Machining Engineer jobs at Fetch Rewards

SeatGeek believes live events are powerful experiences that unite humans. With our technological savvy and fan-first attitude we're simplifying and modernizing the ticketing industry. SeatGeek is a technology innovator on a mission to disrupt the $300 billion ticketing industry. We have the product, vision, and team to make life better for performers, venues, and fans, and build a generational consumer brand in the process. All we're missing is you. You will join a group that bridges the gap between research and production-ready ML systems. Your work will directly impact how millions of fans discover and purchase tickets, how we optimize pricing and inventory, how we personalize the SeatGeek experience, and how we prevent fraud across our marketplace. You will design and build ML infrastructure and services that operate at scale, turning complex algorithms into reliable, fast, and maintainable systems that drive business value. What you'll do Design, build, and deploy machine learning models and systems that operate reliably at scale in production Build and maintain ML infrastructure including feature stores, model serving platforms, and real-time inference pipelines Embed on a product engineering team and collaborate closely with data scientists, PMs ,and Software Engineers to translate research and experimental models into production-ready systems Solve complex technical challenges unique to the ticketing industry, including real-time pricing optimization, demand forecasting, and fraud detection Develop automated ML pipelines for training, validation, deployment, and monitoring using MLOps best practices Work across team and discipline boundaries to evangelize ML capabilities and build them into SeatGeek's core product offerings What you have Experience building and deploying machine learning systems in production environments. We'll be interested in hearing about the systems you've built, the scale you've operated at, and the business impact you've driven 4+ years of experience in software engineering with at least 2+ years focused on machine learning systems and MLOps Strong programming skills in Python and experience with ML frameworks like scikit-learn, TensorFlow, PyTorch, or similar Experience with cloud platforms and containerization technologies Understanding of both batch and real-time ML systems, including experience with model serving, A/B testing, and performance monitoring Passion for software craftsmanship and product. You have well-considered opinions about how systems should be built, and hold yourself and your code to a high standard A product mindset. You think beyond the model accuracy, about user experience, business impact, system reliability, and what makes a great product tick Commitment to your teammates. You enjoy working with a diverse group of people with different experiences and take pride in mentoring and learning from others Our stack You do not need experience with all of these, but we thought you might be curious. What we care about is your experience, skills, and approach to problem solving. Tools can be learned. Languages + Frameworks: Python + FastAPI, Go, C# + .NET Core Datastores: Postgres, MemcachedRedis, Elasticsearch Cloud: AWS (SageMaker, Redshift, ECS), Airflow for orchestration Version control: Gitlab AI Tooling: Cursor, Github Copliot, Claude Code Observability: Datadog Perks Equity stake Flexible work environment, allowing you to work as many days a week in the office as you'd like or 100% remotely A WFH stipend to support your home office setup Unlimited PTO Up to 16 weeks of fully-paid family leave 401(k) matching program Student loan support resources Health, vision, dental, and life insurance Up to $25k towards family building and reproductive health services Gender-affirming care support program $500 per year for wellness expenses Subscriptions to Headspace (meditation), Headspace Care (therapy), and One Medical $120 per month to spend on tickets to live events Annual subscription to Spotify, Apple Music, or Amazon music The salary range for this role is $145,000-$200,000 USD. This role is also equity eligible. Actual compensation packages within that range are based on a wide array of factors unique to each candidate, including but not limited to skill set, years and depth of experience, certifications, and specific location. SeatGeek is committed to providing equal employment opportunities to all employees and applicants for employment regardless of race, color, religion, creed, age, national origin or ancestry, ethnicity, sex, sexual orientation, gender identity or expression, disability, military or veteran status, or any other category protected by federal, state, or local law. As an equal opportunities employer, we recognize that diversity is a positive attribute and we welcome the differences and benefits that a diverse culture brings. Come join us! To review our candidate privacy notice, click here. #LI-Remote

Hightouch is the modern AI platform for marketing and growth teams. Our AI agents reimagine marketing workflows, allowing marketers to create content, plan campaigns, and execute strategies with transformational velocity and performance. Hightouch is a rare company built on the intersection of two fundamental technological shifts: advances in LLMs and agentic AI, and the creation and rapid adoption of cloud data warehouses like Snowflake and Databricks. Building on these tailwinds, we've become a leader in AI marketing and partner with industry leaders like Domino's, Chime, Spotify, Ramp, Whoop, Grammarly, and over 1000 others. Our team focuses on making a meaningful impact for our customers. We approach challenges with first-principles thinking, move quickly and efficiently, and treat each other with compassion and kindness. We look for team members who are strong communicators, have a growth mindset, and are motivated and persistent in achieving our goals. About the Role We're looking to hire a machine learning engineer as we expand our data activation products to include an intelligence layer. While hundreds of companies use Hightouch today to sync data into their SaaS systems to automate and improve operations, there's a lot of surface area we haven't touched in helping companies figuring out which customers to message, what content to put in messages, and when to send messages. A lot of this work today is done manually through intuition and guesswork, and we believe that adding machine learning could have a step function impact for our customers. And given our access to data warehouses and databases, Hightouch is perfectly placed to make use of a company's customer data in building a powerful intelligence layer. Some of the problems we'll be working on include: Personalization and Product Recommendation: There are often many options for what content a company could message a user with, including which products to show from catalogues. Given this large state space, how can Hightouch help personalize messages with the most relevant content for each user? Automated Experimentation: Helping companies intelligently navigate and automate experiments across the extensive number of options for messaging customers. Predictive Audiences: Building models to predict which users are most likely to convert, churn, or take desired actions. Content Generation: Particularly with recent advances in LLMs, how can we help marketers generate text, images, and creatives that are compelling to their customers? Budget Optimization: Helping companies assess which marketing spend is driving the most incremental conversions, and where the marginal CAC is lowest. As an early machine learning engineer, you will help build comprehensive solutions to the above domains from scratch. Responsibilities will be highly varied and include working on customer research, problem definition, predictive modeling, machine learning infrastructure, and partnering with customers. We are looking for talented, intellectually curious, and motivated individuals who are interested in tackling the problems above. This is a senior role, but we focus on impact and potential for growth more than years of experience. The salary range for this position is $200,000 - $260,000 USD per year, which is location independent in accordance with our remote-first policy. Interview Process Our interview process focuses on evaluating fit for the most important dimensions of the role: product sense, ability to architect backend and distributed systems, and alignment with Hightouch's values. Notably, we don't do any programming interviews as we believe they are low signal to noise and aren't a good evaluation mechanism. Intro Call [15-30m]: Introductory call with either a member of our recruiting team or the hiring manager to get to know each other and see if the role could be a good mutual fit. System Design Screen [45m]: Designing a data processing feature end-to-end. Machine Learning Modeling Interview [90m]: Designing a predictive model end-to-end, including data collection and preparation, model training and evaluation, and what systems would be needed to run the model in production. System Design Interview [90m]: Work with the interviewer to architect a system at a conceptual level. The problem will be at a pretty high level - and have both product and customer requirements as well as technical. Hiring Manager Interview [30m]: Chat with hiring manager about past experiences and future operating preferences to assess fit on company values and operating principles.

This role is with Mercor. Mercor uses RippleMatch to find top talent. At Mercor, we're building the talent engine that helps leading labs and research orgs move AI forward. Our latest initiative focuses on benchmarking and improving model performance and training speed across real ML workloads. If you're an early-career Machine Learning Engineer or an ML PhD who cares about innovation and impact, we'd love to meet you. What to Expect As a Machine Learning Engineer, you'll tackle diverse problems that explore ML from unconventional angles. This is a remote, asynchronous, part-time role designed for people who thrive on clear structure and measurable outcomes. Schedule: Remote and asynchronous-set your own hours Commitment: ~20 hours/week Duration: Through December 22nd, with potential extension into 2026 What You'll Do Draft detailed natural-language plans and code implementations for machine learning tasks Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments Identify failure modes and apply golden patches to LLM-generated trajectories for machine learning tasks What You'll Bring Experience: 0-2 years as a Machine Learning Engineer or a PhD in Computer Science (Machine Learning coursework required) Required Skills: Python, ML libraries (XGBoost, Tensorflow, scikit-learn, etc.), data prep, model training, etc. Bonus: Contributor to ML benchmarks Location: MUST be based in the United States Compensation & Terms Rate: $80-$120/hr, depending on region and experience Payments: Weekly via Stripe Connect Engagement: Independent contractor How to Apply Submit your resume on Mercor's website Complete the System Design Session (< 30 minutes) Fill out the Machine Learning Engineer Screen (

#TeamNextdoor Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 340,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com. Meet Your Future Neighbors At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform including our newsfeed, our notifications, and our ads relevance. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be an integral part of making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live. At Nextdoor, we offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The Impact You'll Make You will be part of a scrappy and impactful team building data-intensive products, working with data and features. You will help build the foundational Machine Learning (ML) infrastructure that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform. You should be comfortable with petabytes of data, writing crisp design documentation, and building, debugging, and maintaining highly available distributed systems. The Machine Learning platform that you build will empower developers throughout Nextdoor to build better ML products more quickly than ever before. Your responsibilities will include: You will design, implement and integrate the next generation of Machine Learning infrastructure to empower our Data Scientists and Machine Learning engineers to build machine learning (ML) models that make real-time decisions for the Nextdoor platform You will collaborate with other engineers and data scientists to create optimal experiences on the Core ML platform, including but not limited to: the featurestore, the real-time serving layer and the offline training system What You'll Bring To The Team Master / Ph.D. in Computer Science, Applied Math, Statistics, Engineering or a related field 3+ years of industry experience of applying machine learning at scale 3+ years of experience in building performant and scalable backend services Experience with Python, Kubernetes, Go, Kafka, Docker, Spark, SQL, AWS and the Unix environment Experience with machine learning libraries and frameworks like Xgboost, Sklearn, TensorFlow, PyTorch, etc A deep empathy for customer needs and insights as well as an intuitive grasp of the business problems we're trying to solve Extensive experience in one or more of the following languages: Python, Go, Java, or Scala Experience in designing, building, and debugging distributed systems Proven engineering skills. Experience of writing and maintaining high-quality production code A strong ability to partner with other data engineers throughout the company, and consult, design, and review their projects Strong collaboration and communication skills, both verbal and written Ability to succeed in a dynamic startup environment Eagerness to explore and apply AI and emerging technologies to reimagine how work gets done Rewards Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications. Compensation may also vary by geography. The starting salary for this role is expected to range from $205,000 to $336,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date. When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care. At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records. For information about our collection and use of applicants' personal information, please see Nextdoor's Personnel Privacy Notice, found here. #LI-Hybrid

Supportiv is a peer-to-peer mental and emotional well-being platform that provides real-time support for everyday struggles, 24/7/365, at 1/10 the cost of therapy, ensuring true accessibility. Our multi-patented matching process connects users within a minute to dynamically formed, live-moderated peer group chats (max. five users), based on their natural language-expressed needs. As conversations unfold, we intelligently refine our understanding and precision-match users with the most relevant healthcare resources and services in real time using RAG-powered retrieval systems and adaptive agentic flows. Supportiv empowers users to cope, problem-solve, and heal in a highly user-friendly, practical way-outside the constraints of the broken US mental health system-by harnessing advanced AI and modern NLP techniques. Our solutions serve top employers and health plans, including two Fortune 10 companies. 92% of users rate their experience 4 or 5/5 stars, and we provide proprietary outcome measurements unmatched in the industry. Role Description This is a full-time remote role for a Senior Machine Learning Engineer. The Senior Machine Learning Engineer will design, develop, and implement machine learning models and algorithms to improve our AI/NLP-driven support services. Day-to-day tasks will include enhancing our proprietary language models. The role also involves collaborating with cross-functional teams to integrate and optimize machine learning solutions, ensuring operational efficiency and effectiveness. You Highly analytical, creative, and impact-driven Passionate about applying AI and NLP to solve real-world problems Excited about data-driven insights that inform product development and business decisions A strong leader and mentor, eager to grow and guide a team Your Experience 2+ years leading teams and successful projects 7+ years post-grad experience in Deep Learning and NLP Master's degree (PhD preferred) in deep learning, NLP/NLU, or related fields with publications in top-tier journals/conferences Strong expertise in modern NLP approaches, including: Transformers, BERT, GPT Recommendation and RAG systems Agentic workflows and autonomous AI-driven decision-making Contextual AI and multi-modal learning techniques Proficiency with shared NLP libraries and tools: Hugging Face, PyTorch, TensorFlow, LangChain, Scikit-learn, SpaCy, NLTK Experience with cloud computing technologies and scalable AI architectures Proven ability to develop, evaluate, deploy, and monitor NLP models in production Strong communication and collaboration skills Supportiv's Offer Competitive compensation package with equity for eligible roles ($180k-$250k based on location and experience) Comprehensive health benefits (100% employer-paid for you and dependents, including vision & dental) 401 (k) with vested match (for full-time US-based employees) Fully remote, flexible work schedule within US time zones Generous PTO & company-wide breaks Unrestricted, unlimited use of Supportiv's anonymous peer support Learning and development budget (conferences, courses, and professional growth opportunities) In-person team gatherings focused on collaboration and team-building Interview Process [1 day] Take-home programming challenge In-depth technical interviews: [60 min] System design [30 min] Deep learning/NLP interview [30 min] Technical programming interview [30 min] Cultural & values fit debrief with founder/CEO Reference check & offer

Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross-channel interactions, and optimize engagement-all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences. Our success is powered by extraordinary people who bring our core values-Trust, Growth Mindset, Balance, and Humility-to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That's why we've been recognized as one of Inc's Best Workplaces and Fastest Growing Companies, and were recognized on Forbes' list of America's Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront's Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work. With a global presence-including offices in San Francisco, New York, Denver, London, and Lisbon, plus remote employees worldwide-we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let's shape the future of customer engagement together! Position Overview: We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova's agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform. You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands-on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast-moving, cross-functional product environment. Responsibilities: Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers. Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns. Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring. Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently. Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics. Prototype applied ML solutions to validate feasibility before investing in full builds. Ensure secure, robust handling of data used in ML workflows and retrieval operations. Collaborate with product, design, and engineering to align ML system design with user experience and product goals. Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript. Qualifications: 5+ years experience as a Machine Learning Engineer or similar role focused on production systems. Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits. Experience with retrieval systems, vector databases, search technologies, or RAG architectures. Prior work integrating ML or LLM-powered features into production applications. Understanding of ML evaluation techniques, experimentation design, and failure analysis. Ability to lead complex projects, make practical trade-offs, and work independently in areas of ambiguity. Strong communication and collaboration skills in a distributed environment. Bonus Points Experience building ML or LLM platforms, tooling, or developer-facing frameworks. Prior work with embeddings, search-ranking systems, or advanced RAG architectures. Familiarity with event-driven systems or streaming architectures. Experience with model observability, performance monitoring, or proactive regression detection. Background in personalization, recommendations, or applied NLP. Experience working in remote-first engineering teams. Perks & Benefits: Competitive salaries, meaningful equity, & 401(k) plan Medical, dental, vision, & life insurance Balance Days (additional paid holidays) Fertility & Adoption Assistance Paid Sabbatical Flexible PTO Monthly Employee Wellness allowance Monthly Professional Development allowance Pre-tax commuter benefits Complete laptop workstation The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations. Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others. Recruitment Disclaimer: Please be aware that Iterable, Inc. (“Iterable”) and our official professional recruiting agencies and platforms do not: Send job offers from free email services like Gmail, Yahoo mail, Hotmail, etc. Request money, fees, or payment of any kind from prospective candidates to apply to Iterable, for employment, or for the recruitment process (e.g. for home office supplies, or training, etc.). Request or require personal documents like bank account details, tax forms, or credit card information as part of the recruitment process prior to the candidate signing an engagement letter or an employment contract with Iterable. You may see all job vacancies on our official Iterable channels: Official Iterable website, Careers page: ***************************** Official LinkedIn Jobs page: *********************************************** Iterable is not affiliated in any way to these impostors and we hereby confirm that such individuals/entities are not authorized, encouraged, or sponsored to act on behalf of Iterable. Such job opportunities are entirely fake and not valid. Therefore, please disregard any written or oral request for a job offer or an interview that you believe is or might be fraudulent or suspicious and immediately reach out to us via email at *********************** upon receiving a suspicious job offer. Criminal and/or civil liabilities may arise from such actions, and Iterable expressly reserves the right to take legal action, including criminal action, against such individuals/entities whenever such phenomena occur. In any case, please note that under no circumstances shall Iterable and any of its affiliates be held liable or responsible for any claims, losses, damages, expenses or other inconvenience resulting from or in any way connected to the actions of these impostors. Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.

Iterable is the leading AI-powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross-channel interactions, and optimize engagement-all with enterprise-grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences. Our success is powered by extraordinary people who bring our core values-Trust, Growth Mindset, Balance, and Humility-to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That's why we've been recognized as one of Inc's Best Workplaces and Fastest Growing Companies, and were recognized on Forbes' list of America's Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront's Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work. With a global presence-including offices in San Francisco, New York, Denver, London, and Lisbon, plus remote employees worldwide-we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let's shape the future of customer engagement together! How you will make an impact: We're looking for a talented Senior Machine Learning Engineer to join a cross-functional machine learning team shaping the future of our platform's AI capabilities. In this role, you'll architect and develop robust systems for feature engineering and large-scale model training - collaborating across teams, navigating complex data challenges, and guiding technical direction. This is an exceptional opportunity for someone with a strong platform mindset who is passionate about building end-to-end ML workflows, enjoys tackling real-world data problems, and thrives on ownership from ideation through to deployment. You'll play a pivotal part in designing reusable, scalable ML infrastructure, enabling teams to accelerate experimentation and bring intelligent features to life. While specific domain expertise in certain ML methods is a plus, what matters most is your ability to identify impactful opportunities, prototype new solutions, and continuously advance our platform's machine learning capabilities. One of our core values is a growth mindset and Iterable is a company where everyone can grow. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description. How You Will Make a Difference: Independently lead large-scale machine learning initiatives-delivering capabilities for scalable feature engineering, data processing, and model training on Databricks. Design, build, and deploy machine learning models that enable our partners to reach the right user with the right message at the right time. Own the complete lifecycle of ML platform features: from requirements gathering and architecture, through implementation, deployment, and post-launch support. Shape architectural decisions aimed at building robust, reusable, and highly available ML infrastructure that raises the bar for engineering and data science excellence. Mentor colleagues through code reviews, technical design sessions, and knowledge sharing, helping grow a strong culture of engineering rigor and learning. We Are Looking for People Who: Have 5+ years of experience in machine learning engineering, data infrastructure, or platform engineering, preferably in a SaaS environment. Demonstrate a strong track record leading multi-stakeholder projects that deliver platform features, scalable ML tooling, or end-to-end training systems. Show proficiency with Python (with a preference for experience in distributed data processing environments like Databricks, Spark, or similar platforms). Bring hands-on experience with large-scale data pipelines, distributed systems, and cloud data storage (Databricks Delta, Spark, Kafka, Postgres, etc.). Exhibit a product-minded approach: comfortable partnering with product managers and data practitioners to balance trade-offs across usability, scalability, and complexity. Possess curiosity and adaptability to master new ML and data technologies, frameworks, and best practices. Communicate and collaborate effectively within remote and distributed teams. Bonus Points Experience building or operating ML platforms on Databricks. Scala development experience Familiarity with ML workflow orchestration tools (e.g., MLflow, Kubeflow, Airflow) and interest in automating model development, testing, and deployment. Exposure to generative AI or large language model workflows within an agentic or conversational UX context. Experience designing developer-facing APIs or tools to empower other ML engineers or data scientists. Success working in remote-first or globally distributed engineering organizations. Perks & Benefits: Competitive salaries, meaningful equity, & 401(k) plan Medical, dental, vision, & life insurance Balance Days (additional paid holidays) Fertility & Adoption Assistance Paid Sabbatical Flexible PTO Monthly Employee Wellness allowance Monthly Professional Development allowance Pre-tax commuter benefits Complete laptop workstation The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations. Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others. Recruitment Disclaimer: Please be aware that Iterable, Inc. (“Iterable”) and our official professional recruiting agencies and platforms do not: Send job offers from free email services like Gmail, Yahoo mail, Hotmail, etc. Request money, fees, or payment of any kind from prospective candidates to apply to Iterable, for employment, or for the recruitment process (e.g. for home office supplies, or training, etc.). Request or require personal documents like bank account details, tax forms, or credit card information as part of the recruitment process prior to the candidate signing an engagement letter or an employment contract with Iterable. You may see all job vacancies on our official Iterable channels: Official Iterable website, Careers page: ***************************** Official LinkedIn Jobs page: *********************************************** Iterable is not affiliated in any way to these impostors and we hereby confirm that such individuals/entities are not authorized, encouraged, or sponsored to act on behalf of Iterable. Such job opportunities are entirely fake and not valid. Therefore, please disregard any written or oral request for a job offer or an interview that you believe is or might be fraudulent or suspicious and immediately reach out to us via email at *********************** upon receiving a suspicious job offer. Criminal and/or civil liabilities may arise from such actions, and Iterable expressly reserves the right to take legal action, including criminal action, against such individuals/entities whenever such phenomena occur. In any case, please note that under no circumstances shall Iterable and any of its affiliates be held liable or responsible for any claims, losses, damages, expenses or other inconvenience resulting from or in any way connected to the actions of these impostors. Iterable is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Iterable does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender-identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Iterable also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Pursuant to the San Francisco Fair Chance Ordinance and other similar state laws and local ordinances, and its internal policy, Iterable will also consider for employment qualified applicants with arrest and conviction records.

Come build at the intersection of AI and fintech. At Ocrolus, we're on a mission to help lenders automate workflows with confidence-streamlining how financial institutions evaluate borrowers and enabling faster, more accurate lending decisions. Our AI-powered data and analytics platform is trusted at scale, processing nearly one million credit applications every month across small business, mortgage, and consumer lending. By integrating state-of-the-art open- and closed-source AI models with our human-in-the-loop verification engine, Ocrolus captures data from financial documents with over 99% accuracy. Thanks to our advanced fraud detection and comprehensive cash flow and income analytics, our customers achieve greater efficiency in risk management, and provide expanded access to credit-ultimately creating a more inclusive financial system. Trusted by more than 400 customers-including industry leaders like Better Mortgage, Brex, Enova, Nova Credit, PayPal, Plaid, SoFi, and Square-Ocrolus stands at the forefront of AI innovation in fintech. Join us, and help redefine how the world's most innovative lenders do business. Summary As a Staff Machine Learning Engineer at Ocrolus, you'll be a hands-on technical leader who helps shape the future of our machine learning systems. This is a high-impact role, entailing strategic responsibility in determining the company's Machine Learning infrastructure, system architecture, and deployment protocols. You will collaborate across teams to design, scale, and refine models that power core features - from document understanding and OCR to complex NLP and decision intelligence. This role involves the design of scalable Machine Learning solutions, mentorship of engineering personnel, and contribution to the technical and organizational advancement of the AI stack. The ideal candidate will excel in addressing complex challenges, providing guidance to others, and spearheading innovation on a large scale. What you'll do: Spearhead the Design and Architecture: Lead the design and architecture of robust, scalable machine learning systems that are primed for seamless deployment into production. Enhance Productivity: Design and implement essential machine learning infrastructure and tools that support multiple teams, streamlining workflows and improving efficiency across the organization Solve Complex Infrastructure and ML Problems: Address complex infrastructure and machine learning challenges that span the organization. Analyze systems to identify and rectify bottlenecks, inefficiencies, and areas for improvement. Drive Model Evaluation and Optimization: Lead the development of model evaluation frameworks, optimize data pipelines, and implement continuous training strategies to ensure that models remain accurate and up-to-date. Apply ML Expertise to Fintech: Leverage state-of-the-art machine learning models within the fintech domain to automate and enhance document processing. Collaborate Across Teams: Work closely with stakeholders from Product, Engineering, and Operations to ensure that goals are aligned and that execution is coordinated and effective. Mentor and Guide Engineers: Provide mentorship to engineers within both ML and platform teams, fostering their professional development and contributing to the overall growth of Ocrolus' technical expertise. Coach and influence others to improve company culture. Contribute to Engineering Standards: Play an active role in shaping Ocrolus-wide engineering standards, participate in design reviews (RFCs/ADRs), and promote adherence to best practices. Champion Code Quality and Reliability: Be a vocal advocate for code quality, observability, and system reliability. This includes everything from implementing rigorous A/B testing to setting up real-time monitoring systems. Understand how their team and projects fit into the larger business goals. Bring together technical and nontechnical stakeholders towards common objectives, suggest alternative solutions to customer problems, and help teach and support more junior teammates. Look for opportunities for process improvements within their team and works with others to implement process changes. Find ways to incorporate company values into day-to-day decisions and have ideas on how to build policies/processes that support the improvement of company culture. Who we're looking for: (Skill Sets and Qualifications) Bachelor's or Master's degree in Computer Science, Machine Learning, Applied Mathematics, or a related technical field; PhD preferred. 7+ years of experience developing and deploying machine learning models in production environments, with a focus on real-world applications and measurable impact. Deep expertise in Python and at least one major ML framework (e.g., PyTorch, TensorFlow); strong proficiency in building, training, and optimizing deep learning models. Proven experience in applying ML techniques to computer vision, OCR, or NLP problems, ideally at scale and in latency-sensitive environments. Strong understanding of ML system design, including model evaluation, A/B testing, continuous training, and monitoring in production. Solid engineering fundamentals - data structures, system design, version control, and testing - with a history of writing clean, maintainable, and scalable code. Experience with modern infrastructure tools and cloud platforms (Docker, Kubernetes, Helm, AWS/GCP); comfortable navigating MLOps pipelines and deployment workflows. Demonstrated ability to lead cross-functional initiatives, influence architectural decisions, and communicate complex technical ideas to diverse stakeholders. Experience mentoring engineers and fostering a culture of high standards, curiosity, and ownership. Preferred Attributes: Working familiarity with additional programming languages (e.g., Go, Java, or Scala) is a plus. Experience operating within regulated industries (fintech, healthtech, etc.). Active contributor to open source, research publications, or public tech community. Champions a culture of humility, curiosity, and ownership in technical decision-making. Note: The full-time salary range for this role is around $200,000 + equity + benefits. Base pay offered may vary depending on job-related knowledge, skills, experience, and market location. Disclosure as required by N.Y.C. Admin. Code §§ 8-102 and 8-107(32) of the full time salary compensation range for this role when being hired into our offices in New York City. Life at Ocrolus We're a team of builders, thinkers, and problem solvers who care deeply about our mission - and each other. As a fast-growing, remote-first company, we offer an environment where you can grow your skills, take ownership of your work, and make a meaningful impact. Our culture is grounded in four core values: Empathy - Understand and serve with compassion Curiosity - Explore new ideas and question the status quo Humility - Listen, be grounded, and remain open-minded Ownership - Love what you do, work hard, and deliver excellence We believe diverse perspectives drive better outcomes. That's why we're committed to fostering an inclusive workplace where everyone has a seat at the table, regardless of race, gender, gender identity, age, disability, national origin, or any other protected characteristic. We look forward to building the future of lending together.

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI. Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta. About the role: At Cresta, we are dedicated to building state-of-the-art Machine Learning systems that leverage Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and other AI techniques to power our products. Our team develops models and platforms that process complex data, extract meaning, and deliver real-time, actionable intelligence at scale. By combining cutting-edge research with scalable engineering, we enable organizations to make data-driven decisions and unlock the full potential of AI in their workflows.A key focus of this role is designing and developing agentic AI workflows that empower users to dynamically interact with machine learning systems, refining and guiding the discovery process in an iterative and interactive manner. You will also design and implement evaluation frameworks to assess model performance, reliability, and usability in real-world applications. Our goal is to provide intelligent, context-aware AI systems-enhanced by RAG techniques-that deliver accurate insights, adapt to user needs, and integrate seamlessly into enterprise applications.As a Machine Learning Engineer, you will be at the forefront of applying modern ML and NLP techniques to solve complex challenges. Your work will focus on building robust, scalable AI solutions, developing RAG-powered systems, evaluating LLMs, and creating real-time, agent-driven workflows that bring AI into the hands of our customers in powerful and intuitive ways. Responsibilities Build and optimize agentic AI workflows that enable users to dynamically interact with and refine outputs from ML systems. Research and implement advanced ML and NLP techniques, including transformer-based models, embeddings, and retrieval-augmented generation. Develop evaluation frameworks to assess accuracy, robustness, and usability of ML/LLM models in production environments. Design, train, and deploy machine learning models for tasks such as classification, entity identification, information extraction, retrieval, topic discovery, and structured insight generation. Architect and optimize RAG pipelines for grounding LLMs with enterprise data to ensure accuracy and reliability. Collaborate with engineers, UX designers, and product managers to integrate AI-driven capabilities into Cresta's platform. Optimize ML pipelines and data processing systems to operate efficiently at scale. Qualifications We Value Master's or Ph.D. in Computer Science, Machine Learning, AI, or a related field. 5+ years of hands-on experience building and deploying ML models in production. Strong knowledge of ML frameworks and NLP libraries (e.g., PyTorch, TensorFlow, Hugging Face, spa Cy, NLTK). Solid experience with modern ML techniques including transformer architectures, embeddings, retrieval systems, and large-scale model training. Experience designing and deploying Retrieval-Augmented Generation pipelines for enterprise use cases. Familiarity with evaluation and benchmarking frameworks for ML/LLM models. Strong passion for AI-driven innovation, with a proven ability to deliver impactful, production-grade solutions. Perks & Benefits: We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family's needs Paid parental leave to support you and your family Monthly Health & Wellness allowance Work from home office stipend to help you succeed in a remote environment Lunch reimbursement for in-office employees PTO: 3 weeks in Canada Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details. We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from ************** domain. Any outreach claiming to be from Cresta via other sources should be ignored. If you are uncertain whether you have been contacted by an official Cresta employee, reach out to ********************

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi! About Quantiphi Quantiphi is an award-winning Applied AI and Big Data software and services company, driven by a deep desire to solve transformational problems at the heart of businesses. Our signature approach combines groundbreaking machine-learning research with disciplined cloud and data-engineering practices to create breakthrough impact at unprecedented speed. Company Highlights: Quantiphi has seen 2.5x growth YoY since its inception in 2013, we don't just innovate-we lead. Headquartered in Boston, with 4000+ Quantiphi professionals across the globe. As an Elite/Premier Partner for Google Cloud, AWS, NVIDIA, Snowflake, and others, we've been recognized with: 17x Google Cloud Partner of the Year awards in the last 8 years 3x AWS AI/ML award wins 3x NVIDIA Partner of the Year titles 2x Snowflake Partner of the Year awards We have also garnered Top analyst recognitions from Gartner, ISG, and Everest Group. We offer first-in-class industry solutions across Healthcare, Financial Services, Consumer Goods, Manufacturing, and more, powered by cutting-edge Generative AI and Agentic AI accelerators. We have been certified as a Great Place to Work for the third year in a row- 2021, 2022, 2023. Be part of a trailblazing team that's shaping the future of AI, ML, and cloud innovation. Your next big opportunity starts here! Job Overview: We are looking for a Machine Learning Engineer with strong expertise in Google Cloud AI tools, ML model development, and end-to-end deployment. The ideal candidate will have hands-on experience with Google Cloud Document AI, Vertex AI, and Large Language Models (LLMs). You will be responsible for designing, training, evaluating, and fine-tuning ML models, integrating them with cloud-based applications, and ensuring scalable and reliable performance in production environments. Key Responsibilities: Design, develop, train, and fine-tune machine learning models, including custom and pre-trained models on Google Cloud Vertex AI and Document AI. Build and manage custom Document AI processors such as Custom Document Splitter, Custom Document Classifier, and Custom Document Extractor. Work with pre-trained Document AI processors and customize them for business-specific document understanding tasks. Develop and deploy ML solutions using GCP services like Cloud Functions, Cloud Run, Firestore, Cloud SQL, Cloud Storage, and BigQuery. Design and implement data preprocessing pipelines for large-scale, unstructured, and semi-structured data. Integrate ML models into production systems via secure and scalable APIs. Evaluate model performance using standard ML metrics, perform model validation, and optimize for accuracy, latency, and efficiency. Collaborate with cross-functional teams (Data Engineers, Software Developers, and Product Teams) to ensure seamless model integration and delivery. Troubleshoot and debug ML pipelines, training jobs, and model deployment issues. Maintain proper version control of code, models, and configurations using Git/GitHub. Follow best practices for ML lifecycle management, testing, and documentation. Basic Qualifications (Essential): Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent practical experience. Proven experience with Google Cloud Document AI (Custom Workbench: Splitter, Classifier, Extractor, and pre-trained processors). Hands-on experience with Google Cloud Vertex AI for model training, tuning, and deployment. Strong understanding and practical experience with Large Language Models (LLMs) and their fine-tuning. Proficiency in Python and ML libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Experience with ML model design, training, testing, evaluation, and fine-tuning. Solid experience in data preprocessing and feature engineering. Familiarity with GCP services such as Cloud Functions, Cloud Run, Firestore, Cloud Storage, Cloud SQL, and BigQuery. Strong understanding of API integration for ML model deployment. Proficiency in troubleshooting and debugging ML-related issues. Experience with Git/GitHub for version control and collaboration. Other Qualifications (Good to Have): Knowledge of MLOps practices for automating ML workflows, model versioning, and continuous deployment. Experience building and exposing ML models via FastAPI or similar frameworks. Familiarity with data pipeline orchestration tools (e.g., Airflow, Kubeflow). Understanding of security and compliance best practices in ML systems. Strong analytical, problem-solving, and communication skills. What is in it for you: Be part of the fastest-growing AI-first digital transformation and engineering company in the world Be a leader of an energetic team of highly dynamic and talented individuals Exposure to working with fortune 500 companies and innovative market disruptors Exposure to the latest technologies related to artificial intelligence and machine learning, data and cloud If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !

Entefy's Senior Machine Learning Engineer is a highly visible position internally and externally. This is where your deep experience and great insights intersect with an amazing opportunity to shape the future of communication and digital interaction. Skills and Experience:We're not looking for “good.” Entefy is on a mission for best. The success of this mission depends on its team members to be creatively analytical, insatiably curious, and absolutely fearless in tackling big challenges. Requirements: 5+ years of experience in Machine Learning tools and algorithms specially in unstructured data classification and clustering Proficient knowledge of and experience with AI systems Demonstrable expertise in multiple programming languages such as Python, C++, Java, etc. Masters or PhD in Computer Science, Machine Learning, or related field preferred Proficiency in Machine Learning open source tools Proficiency in Machine Translation Proficiency in Social Text Mining Proficiency in SQL and non-SQL databases Proficiency in Data Visualization tools Visit ************** and **************/blog

Entefy's Machine Learning Engineer is a highly visible position internally and externally. This is where your deep experience and great insights intersect with an amazing opportunity to shape the future of communication and digital interaction. Skills and Experience:We're not looking for “good.” Entefy is on a mission for best. The success of this mission depends on its team members to be creatively analytical, insatiably curious, and absolutely fearless in tackling big challenges. Requirements 5+ years of experience in Machine Learning tools and algorithms specially in unstructured data classification and clustering. Demonstrable expertise in MATLAB. Proficient knowledge of and experience with AI systems. Demonstrable expertise in multiple programming languages such as Python, C++, Java, etc. Fluency in English and, at least, 1 other language. Masters or PhD in Computer Science in Machine Learning or related field preferred. Proficiency in Machine Learning open source tools. Proficiency in Machine Translation. Proficiency in Social Text Mining. Proficiency in SQL and non-SQL database. Proficiency in Data Visualization tools. Visit ************** and **************/blog

Attentive is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We're the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights. Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter's work with us to enable billions of interactions that power tens of billions in revenue for our customers. With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive's team has been consistently recognized for its performance and culture. We're proud to be included in Deloitte's Fast 500 (four years running!), LinkedIn's Top Startups, Forbes' Cloud 100 (five years running!), and Inc.'s Best Workplaces. About the RoleOur Machine Learning Engineering team powers personalized experiences for hundreds of millions of customers across thousands of brands. We build advanced ML models that predict customer behaviors in real-time, enabling highly personalized shopping experiences. Joining our team offers a high-growth career opportunity to work with some of the world's most talented machine learning engineers in a high-performance and high-impact culture. We are seeking a self-driven and highly motivated Machine Learning Engineer to join our growing machine learning teams. As an early hire, you will contribute to the development of machine learning models and infrastructure needs across the Attentive platform and work with Product Management and Engineering to implement end-to-end modeling use cases.What You'll Accomplish Define the long-term technical vision for machine learning systems at Attentive, setting the standard for quality, scalability, and innovation Architect and build production-grade ML systems that deliver personalization at scale and in real time Lead cross-functional initiatives across ML, data, and engineering teams to accelerate the deployment and reliability of ML-powered features Proactively safeguard model and system quality by implementing rigorous testing, monitoring, and validation pipeline Champion best practices in ML development, driving improvements to model performance, system resilience, and engineering efficiency Act as a mentor and thought leader - guiding engineers, influencing architecture decisions, and advocating for long-term technical excellence Thrive in a high-impact, fast-paced environment, influencing both technical direction and product outcomes Your Expertise Proven experience building and maintaining large-scale ML systems in production environments Deep proficiency in Python and experience with frameworks such as TensorFlow, PyTorch, and xgboost Strong background with data processing and analytics tools including pandas, Spark, SQL, and matplotlib Expertise in designing scalable, automated pipelines for data processing, model training, validation, and deployment Experience leading cross-functional ML projects, collaborating with engineering, product, and analytics teams Strong communication and leadership skills with the ability to influence technical direction across teams What We Use Infrastructure: Kubernetes (AWS EKS), Istio, Datadog, Terraform, Cloudflare, Helm Backend: Java / Spring Boot microservices (Gradle), DynamoDB, Kinesis, Airflow, Postgres, PlanetScale, Redis Frontend: React, TypeScript, GraphQL, Storybook, Radix UI, Vite, esbuild, Playwright ML & Data: Python, Metaflow, HuggingFace 🤗, PyTorch, TensorFlow, Panda You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work. For US based applicants:- The US base salary range for this full-time position is $315,000 - 420,000 annually + equity + benefits- Our salary ranges are determined by role, level and location #LI-EF1 Attentive Company ValuesDefault to Action - Move swiftly and with purpose Be One Unstoppable Team - Rally as each other's champions Champion the Customer - Our success is defined by our customers' success Act Like an Owner - Take responsibility for Attentive's success Learn more about AWAKE, Attentive's collective of employee resource groups. If you do not meet all the requirements listed here, we still encourage you to apply! No job description is perfect, and we may also have another opportunity that closely matches your skills and experience. At Attentive, we know that our Company's strength lies in the diversity of our employees. Attentive is an Equal Opportunity Employer and we welcome applicants from all backgrounds. Our policy is to provide equal employment opportunities for all employees, applicants and covered individuals regardless of protected characteristics. We prioritize and maintain a fair, inclusive and equitable workplace free from discrimination, harassment, and retaliation. Attentive is also committed to providing reasonable accommodations for candidates with disabilities. If you need any assistance or reasonable accommodations, please let your recruiter know.

Lead the Future of Dentistry. Overjet is the world-leader in dental AI. Already, thousands of dental providers and insurers rely on our platform to deliver the best possible care. Now, we're looking for talented people to fulfill our mission: improve oral health for all. Overjet is where builders become leaders. Everyone here loves to make new things: new products, new partnerships, new content, and a new category of AI technology. And as Overjet grows ridiculously fast, so will you. Simply put, there's no better place to accelerate your career. Come join us! The Role As a Staff ML Engineer at Overjet, your aim will be to lead the development of tools, infrastructure, processes, and overall systems that enable us to develop, test, ship and operationalize AI/ML models into large scale production environments. You will be responsible for designing the architecture and roadmap of the full-stack of ML lifecycle: from dataset creation and pre- and post-processing, model training, and model evaluation to the fully automated CI/CD process for seamless deployment of models and ML solutions in production. As part of your role, you will also be responsible for the development, implementation, and maintenance of tools and systems dedicated to monitoring the performance of our production models. You thrive in uncertainty and are comfortable building entire cloud pipelines from the ground up, leveraging the latest technologies. At Overjet, we are at the forefront of ML/AI innovation, where creative problem-solving and a strong grasp of first principles are essential. We are focused on building future-ready solutions today. Responsibilities Design, develop, and maintain machine learning model development pipelines Design, develop, and maintain real-time and batch inference pipelines Design, implement, and maintain metrics for infrastructure observability and ML model performance Design and develop APIs for model training and inference services, develop and maintain datasets and feature stores Model performance optimization, monitoring, maintenance, and reporting Participating in an on-call rotation, responding to critical incidents outside of normal business hours Qualifications 6+ years of experience designing microservices and data processing pipelines at scale 6+ years of experience with Cloud Platform such as GCP, AWS or Azure Experience with distributed model training and/or inference Experience with deploying applications on Kubernetes, DevOps/GitOps tools such as Terraform, ArgoCD, Crossplane Strong programming skills in Python, Go (Golang), C++ or Java (10+ years) Extensive experience with database (SQL and NoSQL) systems such as BigQuery, Postgres, MongoDB Experience with optimizing models for production deployments (e.g., architecture modifications, quantization, or other techniques) Strong understanding of machine learning concepts and algorithms, and experience with developing and deploying machine learning models in production Working machine learning knowledge of either Computer Vision models or LLMs (Demonstrable experience working with Pytorch is required) Ability to modify and train open source models Why Overjet? Competitive Compensation and Equity Hybrid workplace that provides flexibility, vibrant in-person workspaces, and the ability to build strong connections across all of Overjet - regardless of location 401k plans with a matching program Medical, Dental and Vision coverage: 99% employee premium covered, 75% dependent premium covered Life and AD+D Insurance 8 weeks Paid Parental Leave Optional HSA with Employer contribution Flexible Time Off and company paid holidays Annual Learning and Development Stipend Work from Home Stipend Our Hybrid Workplace We have a unique hybrid workplace at Overjet - which combines the teamwork of meeting in person, with the flexibility of working from anywhere. Many of our positions are based in San Mateo, New York City, Boston, Salt Lake City, and Lahore. The Jetsetters who live in these “geo-hubs” come to the office on Tuesdays and Wednesdays, while having the option to work from home the rest of the week. Our People Team is happy to answer any questions about what hybrid work means for your specific role! Overjet's Values Excellence: We set ambitious goals and strive for excellence. Velocity: We focus, act with urgency, and deliver results. Ownership: We take ownership, dive deep and solve problems. Win-win: We play to win, setting ourselves and our customers up for success. Growth: We stay curious, seek feedback, and continuously learn and grow. Company Recognition Honored as one of the 2025 Best Places to Work by Built In and 2024 Best Places to Work by Built In Named one of the TIME Best Inventions of 2024 Recognized in Newsweek 's Most Loved Workplaces in America 2024 Won the Dental Health category at the Digital Health Awards 2024 and 2024 Best Places to Work by Built In Recognized as one of the Top Startups of 2023 by LinkedIn Named one of the 2023 World's Most Innovative Companies by Fast Company Included on the definitive 2022 Forbes AI 50 Featured in Bloomberg , Forbes , Fast Company , and TechCrunch EEOC Overjet is an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences. Even if you don't meet 100% of the qualifications for this job, we strongly encourage you to apply! If you are a Colorado resident: Please contact us by emailing ********************* to receive compensation and benefits information for this role. Please include the job title in the subject line of the email.

At Underdog, we make sports more fun. Our thesis is simple: build the best products and we'll build the biggest company in the space, because there's so much more to be built for sports fans. We're just over five years in, and we're one of the fastest-growing sports companies ever, most recently valued at $1.3B. And it's still the early days. We've built and scaled multiple games and products across fantasy sports, sports betting, and prediction markets, all united in one seamless, simple, easy to use, intuitive and fun app. Underdog isn't for everyone. One of our core values is give a sh*t. The people who win here are the ones who care, push, and perform. If that's you, come join us. Winning as an Underdog is more fun. About the role and why it's unique: As a Machine Learning Engineer on the Data Engineering team, you'll partner closely with the Data Science team to build out our foundational Machine Learning platform Build internal tools and services to accelerate UD's model building and deployment process Build frameworks to measure and analyze model performance and accuracy in production environments Lead technical initiatives, and drive results in a fast-paced, dynamic environment Lead code reviews, provide constructive feedback, and evangelize best practices to maintain code and data quality Keep up to date on emerging ML technologies and trends and focus on iteratively implementing them into Underdog's engineering systems Who you are: At least 3 years of experience with model lifecycle (optimization, training and serving) in a cloud environment Advanced proficiency with Python and SQL Experience with with big data tools including Spark, Flink, Databricks, Snowflake, S3 Strong proficiency with SageMaker, Vertex AI, Databricks, Kubeflow and/or comparable ML platforms or technologies Experience building recommendation systems Highly focused on delivering results for the Data Science team in a fast-paced, entrepreneurial environment Even better if you have: Strong interest in sports Prior experience in the sports betting industry Our target starting base salary range for this position is between $135,000 and $165,000, plus pre-IPO equity. Our comp range reflects the full scale of expected compensation for this role. Offers are calibrated based on experience, skills, impact, and geographies. Most new hires land in the lower half of the band, with the opportunity to advance toward the upper end over time. What we can offer you: Unlimited PTO for full-time employees (we're extremely flexible with the exception of the first few weeks before & into the NFL season) 16 weeks of fully paid parental leave Home office stipend A connected virtual-first culture with a highly engaged distributed workforce 5% 401k match, FSA, company paid health, dental, vision plan options for employees and dependents #LI-REMOTE This position may require sports betting licensure based on certain state regulations. Underdog is an equal opportunity employer and doesn't discriminate on the basis of creed, race, sexual orientation, gender, age, disability status, or any other defining characteristic. California Applicants: Review our CPRA Privacy Notice here.

Description Function: Engineering, R&D → Data Science / Machine Learning / Operations ResearchAbout PulsePoint:PulsePoint is a fast-growing healthcare technology company (with adtech roots) using real-time data to transform healthcare. We help brands and agencies interpret the hard-to-read signals across the health journey and unify these digital determinants of health with real-world data to produce the most dimensional view of the customer. Our award-winning advertising platforms use machine learning and programmatic automation to seamlessly activate this data, making marketing, predictive analytics, and decision support easy and instantaneous.Sr. Machine Learning Engineer, AdTechAs a member of our Data Science Engineering team, the Sr. Machine Learning Engineer, AdTech will focus on optimizing real-time bidding strategies and auction mechanics to efficiently spend ad budgets and deliver against campaign targets. In addition to the above, you will work with the greater Data Science/Engineering teams on: Analyzing and optimizing real-time bidding strategies and online auction mechanics; Developing new or improving existing models of event predictions; New feature engineering for multiple machine learning models: User embeddings and clustering; fraud detection, etc. Cross-device user identification, cookieless mechanisms development; Mining different data sources; Supporting existing codebase for data integration and production support for our core models. Location: anywhere in the world (End days at around 2pm EST) India, Netherlands, UK: we can hire as FTE Other countries: we can hire as long-term contractor Requirements:5 years minimum of experience in machine learning/data science Key Skills: Python, Algorithms, Optimisation, NLP, Data Mining, Statistical Analysis, Neural Networks, Generalised Linear Regression, Multiclass Classification, Java, R Advanced knowledge of Python using standard DS packages (numpy/pandas/scikit, etc.); Being able to optimize and speed-up code. 3+ years of RTB Auction or similar online technologies. In addition to the above, you'll need to have strong knowledge in the following areas: Algorithms and Data Structures (e.g., sorting, search tree, binary heap, trie; time & mem complexities of algorithms) Probability and Statistics (e.g., hypothesis testing; Markov process and its stationary distributions, stochastic matrix and its properties; Bayesian inference) ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 regularisation, Decision trees and their ensembles, collaborative filtering, Thompson sampling / MCMC, Neural Networks, etc.) Selection Process:1) Initial Screening Call (30 mins)2) Technical Pre-Screening Call with Principal Data Scientist (60 mins)4) Team Interview (around 4-5 hours total)5) WebMD/IB Sr. Tech Leader (30 mins) WebMD and its affiliates is an Equal Opportunity/Affirmative Action employer and does not discriminate on the basis of race, ancestry, color, religion, sex, gender, age, marital status, sexual orientation, gender identity, national origin, medical condition, disability, veterans status, or any other basis protected by law.

About us Mythic is building the future of AI computing with breakthrough analog technology that delivers 100× the performance of traditional digital systems at the same power and cost. This unlocks bigger, more capable models and faster, more responsive applications-whether in edge devices like drones, robotics, and sensors, or in cloud and data center environments. Our technology powers everything from large language models and CNNs to advanced signal processing, and is engineered to operate from -40 °C to +125 °C, making it ideal for industrial, automotive, aerospace, and defense.We've raised over $100M from world-class investors including Softbank, Threshold Ventures, Lux Capital, and DCVC, and secured multi-million-dollar customer contracts across multiple markets. About the role Join us in building the next generation of AI compilers. You'll play a key role in developing the compiler for our novel AI accelerator, working side-by-side with hardware engineers and ML researchers. Your work will shape how deep learning workloads run on cutting-edge dataflow hardware-defining the instruction set, execution model, and developer experience. The result: a compiler that delivers breakthrough performance while remaining seamless and intuitive for ML developers.Here's what you will do Contribute across the full compiler stack, including operator lowering, graph/IR transformations, optimization passes, and backend code generation Optimize for dataflow architectures, developing pipelined schedules, memory orchestration, and resource-constrained execution strategies Collaborate with hardware architects to influence architectural features, ensuring the compiler and hardware evolve together Develop compilation strategies that unify our analog compute with digital subsystems Build and maintain a compiler that produces high-performance binaries with strong debugging support, clear error messages, and predictable performance models Here's the background we hope you will have 3+ years of experience building compilers or high-performance systems software, especially those involving complex resource management or optimization. Expert in modern C++ (C++14/17/20) and strong Python. Experience with compiler IRs (SSA-based or graph-based), transformations, and code generation Exposure to specialized accelerators (GPU, NPU, FPGA, or custom ASIC) or parallel architectures The following would be nice to have, but is not required Experience with machine learning compiler stacks (e.g., ONNX, MLIR, TVM, XLA, IREE, PyTorch), with contributions to MLIR or LLVM projects a plus Experience with optimization methods (LP/MIP, CP, SAT/SMT) using solvers like Gurobi or OR-Tools for scheduling and resource allocation Experience compiling for specialized accelerators (GPU, NPU, FPGA, or custom ASIC) on DNN workloads; GPU/DSP experience is valuable if combined with compiler backend work beyond kernel tuning Familiarity with heterogeneous compilation, especially mixing custom accelerators with CPUs/GPUs/NPUs, and exposure to analog or in-memory compute is a plus Experience collaborating in compiler-hardware co-design (architecture + ISA) for better compiler usability and hardware efficiency What we offer The opportunity to shape how deep learning and LLM workloads are compiled on novel hardware. A role that spans software and hardware co-design, shaping both the compiler and the accelerator architecture A collaborative, innovative team that values engineering rigor, continuous integration, and user-focused design. We foster an environment of shared learning and technical excellence Competitive compensation, equity, and benefits package At Mythic, we foster a collaborative and respectful environment where people can do their best work. We hire smart, capable individuals, provide the tools and support they need, and trust them to deliver. Our team brings a wide range of experiences and perspectives, which we see as a strength in solving hard problems together. We value professionalism, creativity, and integrity, and strive to make Mythic a place where every employee feels they belong and can contribute meaningfully.

Faire is an online wholesale marketplace built on the belief that the future is local - independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town - we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants. By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We're looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours. About the role At Faire we build elegant and efficient products to deliver superior customer experiences and enhance marketplace efficiency at the same time. From the mobile checkout process, to personalized search ranking, to the intelligent underwriting engine that determines credit limits for retailers --- we use data and machine learning to constantly iterate and innovate our product offering to create more value for the ecosystem. Faire is searching for a top-notch staff engineer to lead design and execution as we continue to build our machine learning platform that will power our wholesale marketplace. This role will architect and build scalable, reliable systems to enable seamless software driven machine learning deployment to improve Faire's core metrics. What You'll Do: Design and build highly scalable machine learning systems that the entire company will use. Examples of these include (but are not limited to) “Machine-Learning-as-a-service” Feature store, including batch and real-time feature computation, serving, and monitoring Deep learning infrastructure that powers Faire's language and image models Model prediction services to manage model deployment, inference and monitoring Partner with our internal customers to understand their ML development pain points and craft platform solutions to address them Provide technical mentorship to ML engineers and interns on the team Help shape the long-term strategy and grow the team What it takes: 5+ years experience building production machine learning systems or platform components such as feature store, model training framework, ML prediction service etc Degree in a relevant discipline such as Computer Science, Machine Learning, or another similar field Strong coding skills in Python/Java or equivalent Experience working within common backend system architectures (e.g. microservices) Strong understanding of engineering and infrastructure best practices, general software development principles with a machine learning software development life-cycle orientation Salary Range San Francisco: the pay range for this role is $224,00 to $308,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. Hybrid Faire employees currently go into the office 2 days per week on Tuesdays and Thursdays. Effective starting in January 2026, employees will be expected to go into the office on a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Applications for this position will be accepted for a minimum of 30 days from the posting date. Why you'll love working at Faire We are entrepreneurs: Faire is being built for entrepreneurs, by entrepreneurs. We believe entrepreneurship is a calling and our mission is to empower entrepreneurs to chase their dreams. Every member of our team is taking part in the founding process. We are using technology and data to level the playing field: We are leveraging the power of product innovation and machine learning to connect brands and boutiques from all over the world, building a growing community of more than 350,000 small business owners. We build products our customers love: Everything we do is ultimately in the service of helping our customers grow their business because our goal is to grow the pie - not steal a piece from it. Running a small business is hard work, but using Faire makes it easy. We are curious and resourceful: Inquisitive by default, we explore every possibility, test every assumption, and develop creative solutions to the challenges at hand. We lead with curiosity and data in our decision making, and reason from a first principles mentality. Faire was founded in 2017 by a team of early product and engineering leads from Square. We're backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog. Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form (************************** Privacy For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire's Privacy Notice (******************************

At Philo, we're a group of technology and product people who set out to build the future of television, marrying the best in modern technology with the most compelling medium ever invented - in short, we're building the TV experience that we've always wanted for ourselves. In practice this means leveraging cloud delivery, modern tech stacks, machine learning, and hand-crafted native app experiences on all of our platforms. We aim to deliver a rock solid experience on the streaming basics, while cooking up next generation multi-screen and multi-user playback experiences. Senior Machine Learning Engineer (Recommendation Systems) Philo's recommendation system improves user engagement and customer satisfaction by tailoring content discovery to individual preferences and viewing habits. We want users to be confident that Philo will have something they want to watch every time they open the app. We are seeking a Senior Machine Learning Engineer to lead our content personalization efforts, shaping experiences that impact millions of users. In this role, you will research, design, and build advanced algorithms and large-scale systems that power Philo's recommendation engine. As a senior member of a growing team, you will tackle complex machine learning challenges and collaborate with data science, product, infrastructure, and backend engineering teams to deliver innovative, data-driven personalization solutions. Your work will directly impact content discovery, deepen user engagement, and drive long-term retention. Responsibilities: Lead development of recommendation systems: Design, build, and optimize advanced algorithms for SVOD, Live TV, and FAST personalization. Drive ML innovation at scale: Conduct deep dives into models and system components, ensuring performance, scalability, and robustness across regions and product areas. Own the ML pipeline: Build and maintain reliable pipelines for data extraction, feature engineering, model training, testing, and deployment. Collaborate with Product, Data Science & Engineering: Translate product requirements into ML solutions, set clear expectations, and deliver measurable improvements in user engagement. Advance deep learning in recommendations: Apply frameworks such as TensorFlow, PyTorch, or similar to develop state-of-the-art recommendation models. Experimentation: Conduct rigorous A/B testing and ML experiments to understand model performance and iterate rapidly based on feedback. ML Vision and Roadmap: Contribute to the strategic planning of the recommendations roadmap, aligning engineering efforts with business objectives and user needs. Explore advanced architectures: Experience with frameworks like Two-Tower models and Deep Cross Networks (DCN) is a strong plus. Qualifications: 8+ years of experience in backend engineering and/or data science, including 4+ years focused on machine learning. Experience with recommendation systems is a big plus. Strong coding skills in Python, as well as proficiency in using ML frameworks like PyTorch or TensorFlow. Excellent analytical and problem-solving skills, with the ability to translate complex technical challenges into business solutions. Proven track record of leading projects and delivering impactful machine learning solutions. Strong communication and documentation skills; capable of explaining complex, technical concepts to non-technical stakeholders and to diligently document your work to help the team as a whole learn and move quickly. Experience with Amazon SageMaker or similar MLOps platforms More about Philo At Philo, we're a company that puts people first-both our subscribers and our team. We empower our colleagues to do their best work while supporting one another in pursuing shared goals. We value pragmatism, pride in our work, and passion, with transparency and openness as fundamental parts of our culture. We're committed to diversity, equity, inclusion, and accessibility as we grow the Philo team and shape the future of TV. We believe that a diverse range of voices and perspectives enables us to innovate faster and create the best experiences for our subscribers. Philo is proud to be an Equal Opportunity Employer. We're committed to supporting every candidate and employee. If you need an accommodation at any stage of the process, please email ******************** and we'll work with you to meet your needs. Philo offers 70+ top-rated networks, including AMC, BET, CMT, Comedy Central, Discovery Channel, Food Network, Hallmark Channel, HGTV, HISTORY, Investigation Discovery, Lifetime, MTV, Nickelodeon, OWN, VH1, We TV, and more. It also includes all the groundbreaking originals and blockbuster movies available with AMC+ and access to HBO Max Basic With Ads and discovery+. Our service also includes 100+ free channels and premium add-ons like STARZ and MGM+. Our extensive library boasts over 85,000 titles, and our unlimited DVR allows users to save their favorite shows and movies for up to a year, skipping ads for a seamless viewing experience. Stream on up to three devices simultaneously, whether on your phone, tablet, laptop, or TV using Roku, Apple TV, Fire TV, Samsung TV, Android TV, Vizio TV, or Chromecast. Philo is headquartered in San Francisco, with offices in New York and Cambridge, MA. Our leadership team includes a Facebook co-founder and alums from Meraki and HBO, backed by NEA and industry partners like Discovery, Viacom, AMC, and A&E. Join us at Philo and be part of a team that's shaping the future of TV! Status: Full-time Location: San Francisco, CA or remote within the U.S. Compensation: Includes annual salary, company stock options, and health benefits. Salary is determined by experience and location: San Francisco, New York City: $175K - $235K Boston, DC Metro, Los Angeles, Seattle: $165K - $225K Denver, Atlanta, Austin, Las Vegas, Sacramento, Chicago: $155K - $215K Texas, Florida: $150K - $205K We value a diverse and inclusive workplace and we welcome people of different backgrounds, experiences, skills, and perspectives. Philo is an equal opportunity employer. We believe that everyone does their best work when they are supported by each other and the company, and we offer a generous set of benefits to make sure the Philo team is happy and healthy. Here is a sampling of the benefits we offer our team: Full health, dental and vision coverage for you and your family 401(k) plan with employer contributions (we match 100% of deferrals up to 3% of pay and 50% of the next 2% of pay) Flexible working hours Up to 20 weeks of fully paid parental leave Unlimited paid time off for vacation and sick leave $2,000 annual vacation bonus (we pay you to take a two week vacation) $5,250 annually for professional development and educational assistance $1,250 annual home office + TV stipend during first year of employment ($250 annually thereafter) $500/month ($6,000/year) bonus for employees who commit to working at least 3 days per week in our offices, plus generous commuter benefits ($315/month towards transit, rideshare, bike rental, or parking at our HQ office in San Francisco) Free Gympass subscription - an all-in-one corporate benefit that gives employees the largest selection of gyms, studios, classes, training and wellness apps Dog-friendly office And much more! For California Residents: Philo's CCPA Notice at Collection - Employees, Applicants, Owners, Directors, Officers and Contractors Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.