Member, technical staff jobs in New Brunswick, NJ - 1,623 jobs

Category-defining tech. Career-defining work. Lots of tech companies disrupt. But, many fail when they try to scale. We're different. CockroachDB makes it easier for companies to build and scale apps. This is how and why we're helping some of the most innovative companies on the planet. We tackle problems head-on and focus on solutions that create lasting impact. Because when our customers win, we all win. The Role CockroachDB provides the backbone of storing data on a global scale. Our core mission on the SRE team is to operate at scale a secure & reliable Cockroach Cloud product. We provide consultation, planning, architectural oversight, concrete designs, development, and implementation that improve the resilience, efficiency, performance, and availability of our Cloud Service. We also take pride in being good on-call engineers. We believe regular reflection on the experience of being on-call can contribute in the short, medium, & long term to improvements to the core product, including to CRDB itself. As a Site Reliability Engineer you'll help manage and scale our CockroachCloud service, a fully managed global offering of CockroachDB spanning multiple cloud providers. You will oversee our production system, ensuring that we can provide stable and scalable infrastructure as we deliver CockroachDB to our customers. You Will Manage the infrastructure for cloud services, including running internal production systems and hosting CockroachDB for our external customers. Design, write and deliver software and systems to increase product reliability and operational efficiency. Develop custom tools as necessary. Keep a complex system running and solve problems relating to mission-critical services. Design, implement, operate, and troubleshoot the automation and monitoring of production clusters to maximize performance and availability. Drive the company through disaster recovery tests, where we manually turn down pieces of CockroachDB to test its overall resilience to failures. Participate in an on-call rotation for our production systems and hosted services. The Expectations In your first 30 days, you will onboard and be exposed to our current internal and customer-facing production systems. Working with our existing SRE and engineering teams, you will pair on production operations and build out runbooks for the operation of different systems. We believe that it's essential for you to take this first month to become familiar with our technology and our company. After 3 months, you'll be fully integrated into the team. You will develop and own tooling for reliability, automation, and other issues related to CockroachCloud's stability and scalability. You will identify new opportunities for automating processes, streamlining delivery, deploying new core functionality, and building great tools. You will help make CockroachCloud the best platform to host CockroachDB on by bringing your expertise to our database. You Have Expertise in analyzing, monitoring, and troubleshooting large-scale distributed systems. Experience in software development using one or more of the following: Go, C, C++, Python, Java. Proficiency working with algorithms, data structures, and production troubleshooting. Expertise in working with major cloud providers (AWS, Azure, GCP, etc.) and Cloud APIs. Debugged and optimized code and to automate routine tasks. Working knowledge of web and network protocols and standards (HTTP, TLS, DNS, etc.) Prior on-call experience, exhibiting sense of ownership, attention to detail, and urgency. Experience building collaborative relationships with your colleagues. You enjoy being part of the code review process and partnering with your teammates on challenging problems. The Team We are a group of software engineers first & foremost. We use software engineering as a means to achieve our mission; this is the SRE way. The SRE team is currently distributed across North America (5) and India (4). Reporting to Tom Schmidt - Director, Production Engineering Tom recently joined Cockroach Labs as manager of Site Reliability Engineering and has taken responsibility for Cockroach Cloud's production operations. Tom joined Cockroach Labs after 15 years at IBM where he initially contributed in a wide variety of technical leadership roles, generally focussing on quality and automation across compiler development, test frameworks, CICD, and more. Over the past 7 years, Tom has become an enthusiastic advocate of the Site Reliability Engineering discipline, presenting on the topic at conferences, developing certification curriculum, and securing multiple patents. Tom was also a primary contributor towards the establishment of IBMs formal SRE profession and was recognized as one of the first three SRE Thought Leaders within the company. Most recently, Tom transitioned into a management role where he introduced Site Reliability Engineering to the IBM Business Analytics organization, building an SRE team from the ground up, eventually managing over 20 individuals across 3 unique project areas while establishing practices that now guide over 80 engineers internationally. Cockroach Labs presented a new and unique opportunity to gain experience in a high paced startup environment, laying the foundation for scalable reliability as we prepare for the rapid growth of our Cockroach Cloud offering. Beyond the business, Tom is blessed to call himself a proud father of a 4 year old boy, and otherwise enjoys finding balance between spending time in nature (hiking, camping, exploring) and testing his mettle in competitive gaming. Jordan Lewis - VP, Engineering Jordan is the Head of Engineering for Cockroach Labs. He's responsible for the teams that build, maintain and keep CockroachDB reliably serving the needs of Cockroach Labs' most demanding customer base. He joined Cockroach Labs as a database engineer in 2016 when it was just 25 people before moving into engineering leadership and most recently moving to lead the Cloud organization. Jordan lives in his hometown of Brooklyn NY with his wife. Outside of work he enjoys folk music and riding his electric scooter around town. Cockroach Labs is proud to be an Equal Opportunity Employer building a diverse and inclusive workforce. If you need additional accommodations to feel comfortable during your interview process, please email us at accessibility@cockroachlabs.com. Cockroach Labs has a hybrid work model, with Roachers that are local to one of our offices coming in on Mondays, Tuesdays, and Thursdays and working flexibly the rest of the week. While we've learned valuable lessons working remotely, nothing can replace the connection, creativity, and fun that occurs when Roachers get together and we are committed to fostering a workplace that encourages collaboration and allows us all to do our best work. Benefits Stock Options Medical Insurance Vision Insurance Dental Insurance Life and Disability Insurance Professional Development Funds Flexible Time Off Paid Holidays Paid Sick Days Paid Parental Leave Retirement Benefits Mental Wellbeing Benefits And more! The annual anticipated base salary range for U.S. candidates for this role is listed in USD below. Salary is one component of the Cockroach Labs' Total Rewards package, which also includes, for each employee: stock options, medical insurance, vision insurance, dental insurance, life and disability insurance, funds towards professional development resources, flexible paid time off, 11 paid holidays a year, 10 paid sick days a year, paid parental leave, a 401(k) plan, and wellbeing benefits. We set standard ranges for all U.S.-based roles based on function, level, and geographic location, benchmarked against similar stage growth companies. Actual salaries may vary and fall outside of this range depending on factors such as a candidate's qualifications, geographic location, skills, experience, and competencies. In addition, we are often open to a wide variety of profiles, and recognize that the person we hire may be less experienced (or more senior) than this job description as posted. Salaries for candidates outside the U.S. will vary based on local compensation structures. This position will remain posted until filled. Applicants should apply via our Careers Page. Annual Anticipated Base Salary Range (U.S)$179,000-$236,900 USD

About Us: Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. Companies like Suno, Lovable, and Substack rely on Modal to move from prototype to production without the burden of managing infrastructure. We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno. Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. Our team includes creators of popular open-source projects (e.g. Seaborn, Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience. The Role: We're looking for strong backend engineers who love building a developer tools used by the largest AI companies in the world. You'll be building for things at scale, but also for new AI workflows that change every day. Requirements: * Experience building and shipping modern web applications end-to-end. We care more about what you've built than how many years you've been building. * Comfort working across the stack: TypeScript on the frontend, Python services on the backend, and ClickHouse for data and analytics. * Deep knowledge of observability tools and patterns used for large-scale workloads such as custom sandboxes, training and inference for large language (LLM) and diffusion models. * Experience with at least one of: billing/payments systems, B2B SaaS tooling, or enterprise software, or LLM / diffusion models inference and training loads. * Strong product instincts; you think about customer problems, not just tickets. * Ability to make good tradeoffs between shipping fast and building for scale. * Ability to work in-person in our NYC office.

At Fluidstack, we're building the infrastructure for abundant intelligence. We partner with top AI labs, governments, and enterprises - including Mistral, Poolside, Black Forest Labs, Meta, and more - to unlock compute at the speed of light. We're working with urgency to make AGI a reality. As such, our team is highly motivated and committed to delivering world-class infrastructure. We treat our customers' outcomes as our own, taking pride in the systems we build and the trust we earn. If you're motivated by purpose, obsessed with excellence, and ready to work very hard to accelerate the future of intelligence, join us in building what's next. About the Role As an MTS, Corp IT you will be working across identity, devices, SaaS platforms, and supporting end users. You should be organized, collaborative, and eager to learn while working within established systems and processes. Provide reliable, hands-on IT support for our in office and remote employees by efficiently resolving Help Desk tickets while delivering excellent customer service. Support Fluidstack's MDM fleet comprising mac OS, iOS, and Windows devices. Provide in office support by troubleshooting basic network issues and our A/V systems. Help manage and optimize Okta and our core SaaS tooling by administering and improving integrations and role-based access controls. Support daily procurement and asset management operations by coordinating hardware purchasing and tracking while maintaining accurate asset inventory and device assignments throughout their lifecycle (purchase to decommission). Help maintain clear, organized, and accessible IT documentation by creating easy-to-understand technical documentation for both technical and non-technical audiences. Contribute to IT initiatives by supporting project execution, managing priorities, and ensuring clear communication with stakeholders through regular updates. Help maintain a secure environment by supporting basic security hygiene to include access reviews and basic identity security tasks. Support onboarding and offboarding of Fluidstack employees and contractors. Support the IT team by creating simple, reliable automations that reduce manual work and improve operational efficiency. Qualifications Practical experience administering Okta, including users, groups, and basic app integrations (OIE a plus). Strong knowledge of Google Workspace, with some exposure to Office 365. Hands-on MDM experience with mac OS and Windows, ideally with Iru (formerly Kandji). Ability to support mac OS, iOS, and Windows devices. Familiarity with Atlassian tools (Jira, Confluence) for documentation and project management. Experience participating in procurement and asset management processes. Clear, concise technical writing skills for documentation and knowledge base content. Excellent communication and customer service abilities. Basic understanding of security principles and best practices. Nice To Haves Experience with no‑code/low‑code automation tools (Okta Workflows, n8n, Zapier, Workato, Tray.io). Scripting familiarity with common languages (Bash, PowerShell, Python). Exposure to security and compliance frameworks (SOC 2, ISO 27001, NIST, CIS, FedRAMP). Experience with AI tools, agents, MCPs, automations, and prompting. Fluidstack standardizes on Anthropic Claude and has OpenAI ChatGPT. HRIS integration experience with systems like Deel, Rippling, BambooHR, or Workday. Understanding of API integrations and webhooks, and how to use them effectively. Salary & Benefits Competitive total compensation package (salary + equity). Retirement or pension plan, in line with local norms. Health, dental, and vision insurance. Generous PTO policy, in line with local norms. The base salary range for this position is $90,000 - $150,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options. We are committed to pay equity and transparency. Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans' status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email ********************* with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.

We're assisting a well-funded startup with their search for a Member of Technical Staff - Frontend or Design Engineering. Their product is an open-source platform that creates a feedback loop for optimizing LLM applications - turning production data into smarter, faster, and cheaper models. This role will work onsite in their NY office. The role: The vast majority of your work will be open source. You'll have an opportunity to continue to master your current skills with the flexibility to learn new ones from scratch. If you joined today, you'd take on the open-source UI that helps engineers manage the entire platform operation - think of it like the AWS Console for the platform. The UI streamlines workflows for observability, optimizing (e.g. fine-tuning), evaluations, and more. What you'll bring: Strong technical background - You've tackled hard technical problems. You're comfortable driving large projects from inception to deployment (to start, the observability dashboard). Passionate about your craft & design - You're excited about the idea of re-thinking developer tooling from first principles to build interfaces and workflows that don't just work but also delight. Background in front-end SWE - They've started building POCs using Remix and Tailwind, but ultimately they're not experts in this area (for now!). You'll complement the team with a strong background and technical leadership (esp. React). Hungry for personal growth - There are no speed limits. You're excited about learning and contributing across the stack. In-person in NYC - They work in-person five days a week in NYC. They work hard and obsess about the craft - but maintain and encourage a healthy lifestyle with a long-term mindset.

At Anchorage Digital, we are building the world's most advanced digital asset platform for institutions to participate in crypto. Anchorage Digital is a crypto platform that enables institutions to participate in digital assets through custody, staking, trading, governance, settlement, and the industry's leading security infrastructure. Home to Anchorage Digital Bank N.A., the first federally chartered crypto bank in the U.S., Anchorage Digital also serves institutions through Anchorage Digital Singapore, Porto by Anchorage Digital, and other offerings. The company is funded by leading institutions including Andreessen Horowitz, GIC, Goldman Sachs, KKR, and Visa, with its Series D valuation over $3 billion. Founded in 2017 in San Francisco, California, Anchorage Digital has offices in New York, New York; Porto, Portugal; Singapore; and Sioux Falls, South Dakota. Learn more at anchorage.com, on X @Anchorage, and on LinkedIn. As a member of the Banking Solutions team, you will be responsible for implementing and maintaining innovative products, in a highly collaborative team, that empowers Anchorage's NeoBank functionality. The crypto industry is one of the most exciting industries in tech today, and it is constantly changing! At Anchorage Digital, we are building foundational technology to help the crypto industry evolve in a safe, regulated and highly secure manner, which we believe is essential for maximizing the potential of this exciting industry We think about growth and career development differently at Anchorage Digital. We define performance as acquiring, possessing, and practicing a relevant set of skills and competencies - and the ability to apply them effectively and consistently. We have created the Factors of Growth & Impact to help Anchorage Digital "Villagers" better measure impact and the rich and rewarding learning that happens while exploring, developing, and mastering the capabilities and contributions within and outside of the Fullstack oftware Engineering role. You will be coached, mentored and guided to grow your capabilities in 4 major areas: Technical Skills: * Participate in task breakdown, estimation, design, implementation and maintenance across the full stack. * Build backend services and APIs that power Banking Solutions features. * Create intuitive user experiences that simplify complex financial data into digestible, actionable insights. * Build data visualizations from the ground up (charts, transaction flows, balance reports). * Write, review, test, and document code according to Anchorage's engineering and team standards. * Review code across frontend and backend, ensuring consistency, reducing errors, and sharing context across the engineering team. * Dive deep into complex, ambiguous problems, formulate elegant and practical solutions. Complexity and Impact of Work: * Drive work independently, lead or significantly contribute to medium-to-large projects or processes, usually multi-person interdepartmental or cross-functional projects, including leading from end-to-end with little oversight and coordinating activities of other team members. * Be capable of breaking down large projects into smaller tasks, and accurately estimating the time and scope of projects. Articulate effectively the different options considered, analyzes trade-offs, justifies and recommends priorities. * Foster an efficient deterministic testing culture, with an emphasis on minimizing tech debt. Organizational Knowledge: * Ensure that knowledge is shared among the team and does not position themselves or others as a single point of failure. * Collaborate cross-functionally within the team and other teams at Anchorage Digital * Monitor the development of the company objectives and/or trends that may affect its capacity to succeed. Communication and Influence * Mentor and guide others on the team within their area of specialization or domain, and help others understand the strategic goals of Anchorage and how their work relates to these. * Communicate outside team boundaries to solve problems, network with other teams, and establish positive working relationships in other disciplines and domains. You may be a fit for this role if you: * Have real world experience building complex distributed systems and web applications from scratch. * Experience with backend languages (we mostly use Go, but languages can be learned). * Proficiency with React.JS or similar JavaScript frameworks (Next.JS, Angular.JS, Vue.JS). * Enjoy building resilient services that can handle different volumes of work without manual intervention. * Genuinely care about code quality, test infrastructure, and end-user experience. * Prioritize business value and user experience over "cool tech". * Have developed "computer science fundamentals" (concurrency, algorithms, data structures - formal CS degree NOT required). * Believe software engineering is a team activity and enjoy collaborating, learning from and mentoring others. Although not a requirement, bonus points if you have: * GraphQL and/or gRPC API design and implementation experience (both consuming and building). * Production experience with web security. * A background in the finance industry or fintech. * Experience working across the full stack on customer-facing financial applications. Compensation at Anchorage Digital: * Compensation at Anchorage Digital is market-driven and data-informed. All full-time employees receive a market-leading salary, meaningful equity, and a generous perks and benefits package. * Compensation Range: $189,000-$291,000 - this salary range may be inclusive of multiple regional locations and job grades. This compensation range will be narrowed during the interview process based on skills, abilities, and experience required. We partner with third party firms annually to verify equity, cash, benefits, and perks benchmarks. * Benefits: Anchorage Digital is proud to provide market-leading benefits and perks to our employees. We are only 1% of companies who offer 100% health, dental, and vision coverage for you and your dependents. This means no monthly out-of-pocket premiums for you or your family. We offer a wide range of benefits to our employees globally. * You can learn more about our culture and perks and benefits here. About Anchorage Digital: Who we are The Anchorage Village, what we call our team, brings together the brightest minds from platform security, financial services, and distributed ledger technology to provide the building blocks that empower institutions to safely participate in the evolving digital asset ecosystem. As a diverse team of more than 600 members, we are united in one common goal: building the future of finance by providing the foundation upon which value moves safely in the new global economy. Anchorage Digital is committed to being a welcoming and inclusive workplace for everyone, and we are intentional about making sure people feel respected, supported, and connected at work-regardless of who you are or where you come from. We value and celebrate our differences and we believe being open about who we are allows us to do the best work of our lives. Anchorage Digital is an Equal Opportunity Employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. Anchorage Digital considers qualified applicants regardless of criminal histories, consistent with other legal requirements. "Anchorage Digital" refers to services that are offered either through Anchorage Digital Bank National Association, an OCC-chartered national trust bank, or Anchorage Lending CA, LLC a finance lender licensed by the California Department of Financial Protection and Innovation, License No. 60DBO-11976, or Anchorage Digital Singapore Pte Ltd, a Singapore private limited company, all wholly-owned subsidiaries of Anchor Labs, Inc., a Delaware corporation. Protecting your privacy rights is important to Anchorage Digital, and we work to maintain the trust and confidence of our clients when handling personal or financial information. Please see our privacy policy notices here. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Product TensorZero is building an automated AI engineer (”TensorZero Autopilot”) powered by our open-source LLMOps platform (”TensorZero Stack”). TensorZero Stack We started by building an open-source LLMOps platform for full-stack LLM engineering: Gateway: access every LLM provider through a unified API ( Observability: monitor your LLM systems, programmatically or with a UI Optimization: optimize your prompts, models, and inference strategies Evaluations: benchmark individual inferences or end-to-end workflows Experimentation: deploy with built-in A/B testing, fallbacks, etc. Today, the TensorZero Stack is used by companies ranging from frontier AI startups to Fortune 50 enterprises. TensorZero Autopilot Now we're working on TensorZero Autopilot, an automated AI engineer powered by our open-source LLMOps platform. Think of it like “Claude Code for TensorZero”. TensorZero Autopilot collaborates with engineering teams to automate LLM engineering - with full visibility and control. For example, it can: Analyze millions of inferences to surface error patterns and optimization opportunities Recommend models and inference strategies to improve quality, cost, and latency Generate and refine prompts based on human feedback, metrics, and evaluations Drive optimization workflows like fine-tuning, reinforcement learning, and distillation Set up evaluations, prevent regressions, and align LLM judges to real-world scenarios Run A/B tests to validate changes, identify winners, and close the feedback loop By itself, TensorZero Autopilot drove substantial performance improvements for LLM systems in benchmarks and synthetic environments ranging from data extraction to customer support agents. Role We're looking for a Member of Technical Staff with a background that combines product and engineering. As the first product hire at TensorZero, you'll wear many hats and quickly grow with the company. Early on, the role will be especially focused on our developer community. From coding to content creation, you'll work on whatever it takes to drive adoption: demos, integrations & partnerships, documentation, videos, social media, events, and more. You're a "wartime product manager" who can think outside the box, with the technical background to scale your impact independently. Team & Culture We're a small, deeply technical team based in NYC (in person). As an early contributor, you'll work closely with us and have a significant impact on the project's future and vision. Viraj Mehta (Co-Founder & CTO) is an ML researcher with deep expertise in reinforcement learning and LLMs. He received a PhD from CMU with an emphasis on data-efficient RL for nuclear fusion and LLMs, and previously worked in machine learning at KKR and a fintech startup. He holds a BS in math and an MS in computer science from Stanford. Gabriel Bianconi (Co-Founder & CEO) was the chief product officer at Ondo Finance ($20B+ valuation) and previously spent years consulting on machine learning for companies ranging from early-stage tech startups to some of the largest financial firms. He holds BS and MS degrees in computer science from Stanford. Aaron Hill (MTS) is a back-end engineer with deep expertise in Rust. He became one of the maintainers of the Rust compiler while still in college. Later, he worked on back-end infrastructure at AWS and Svix. He's also an active contributor to many notable open-source Rust projects (e.g. Ruffle). Andrew Jesson (MTS) is an ML researcher with deep expertise in Bayesian ML, causal inference, RL, and LLMs. He recently completed a postdoc at Columbia and previously received a PhD from Oxford, during which he interned at Meta. He has 4k+ citations and several first-author papers at NeurIPS and other top ML venues. Alan Mishler (MTS) is an ML researcher with a background in causal inference, sequential decision making, uncertainty quantification, and algorithmic fairness (1.2k+ citations). Previously, he was an AI Research Lead at JPMorgan AI Research and received a PhD in Statistics from CMU, during which he interned at Google and Box. Shuyang Li (MTS) previously was a staff software engineer at Google focused on next-generation search infrastructure, LLM-based search, and many other specialized search products (local, travel, shopping, maps, enterprise, etc.). Before that, he worked on ML/analytics products at Palantir and graduated summa cum laude from Notre Dame. Simeon Lee (MTS) previously was the Head of Design at Merge from inception through Series B. He was also a founding & senior design engineer at multiple startups in AI and developer tools. Earlier in his career, he worked in investment banking and graduated from USC. _____ You? What We Offer Competitive compensation - We believe that great talent deserves great compensation (salary, equity, benefits), even at an early-stage startup. Open-source contributions - Much of your work will be open-source and public. Learning and growth opportunities - You'll work alongside experts in front-end, back-end, and ML to build high-impact user-facing products. Small, technical, in-person team - You'll work alongside a 100% technical team and help shape our vision, culture, and engineering practices. Best-in-class investors - We're lucky to be have raised $7.3M+ from leading funds like FirstMark (backed ClickHouse), Bessemer (backed Anthropic), Bedrock (backed OpenAI), and many angels. We have years of runway and a long-term mindset. We're Looking For Strong technical background - You've tackled hard technical problems. You can code as needed to scale your impact in product and GTM. Community leadership - You're excited to build a community of developers, teach them about TensorZero, and more. Technical writing & speaking - You're comfortable writing technical content, public speaking, organizing events, and more. Hungry for personal growth - There are no speed limits at TensorZero. You're excited about learning and contributing across the company while wearing many hats. Wartime product manager - "Either you win with grace or by force. But you have to win." TensorZero is a "win by force" company, and you're a "do whatever it takes to win" person. In-person in NYC - We work in-person five days a week in NYC. We work hard and obsess about the craft.

About Us Chakra Labs' mission is to encode human taste into intelligence. We source differentiated, proprietary data from end consumers - giving AI teams access to mission critical datasets for inference and post-training Why you should work with us You will get to touch the latest and greatest technologies across the data, AI, and infrastructure stack. You will get mentored by an experienced and qualified team. Some of our people: Nirmal Krishnan - CEO Formerly: Microsoft, Hedge Fund, Head of Engineering at Artemis. Alex Fung - CTO Formerly: Snap for 5+ years (built Snap Map, led Snap's crypto efforts), Founding Engineer at TipLink You will get paid a very competitive cash package with top benefits and a $30 daily meal stipend. We also provide a compelling equity package. Why you shouldn't work with us This is our life's work. We have fun, but we work hard. If you want to clock a 9-5, this probably isn't a great fit. There's no clear playbook for success. Data and AI are constantly shifting. Adding in a distributed component in terms of sourcing labor - we are constantly learning and shifting. While we have a clear mission and vision, if you're uncomfortable with ambiguity this role will be challenging for you. About You You have a Master / PhD level knowledge of machine learning. You understand the fundamentals of linear algebra, stochastic gradient descent, and can derive linear regression by hand. Post-training & Environments. You are comfortable running SFT across distributed GPU clusters using FSDP. You have an appetite to improve existing models using high-quality data and are capable of reasoning about new environments and online RL (GRPO, PPO). Python (FastAPI, PyTorch, etc.): REST APIs, back-end, vector-math. You can derive some high level abstractions in Torch using lower level primitives. Experience: we don't believe in hard and fast rules here. Roughly 3-5 years of experience is what we're looking for, but more or less experience works as long as the above expectations resonate with you.

Sciemo builds AI for consumer goods: technology that helps businesses make faster, smarter, and more human decisions across the entire IBP process. From optimizing promotions to balancing demand and supply, Sciemo's platform transforms messy, siloed data into measurable business impact. Its AI agents assist decision-makers in real-time, turning complexity into clarity. We are headquartered in New York City. overview We are an industry-leading startup developing AI for consumer brands. Our solutions leverage machine learning, generative AI, agent-based systems, and graph technologies to get our customers to insights in seconds and to business impact in minutes using our products. We are looking for a Founding Member of Technical Staff to join our team guiding the development and deployment of complex ML systems reporting to Dan Wald, Co-Founder & CAIO. role As a Founding Member of Technical Staff, you will work in a hybrid capacity as both a Data Scientist and Machine Learning Engineer, you will play a pivotal role in designing, building, and deploying the intelligence behind our AI products. You'll work across the full spectrum of applied AI-spanning data science, machine learning, and large-scale production engineering. This hybrid role requires both deep expertise in developing innovative models and the engineering discipline to deploy and maintain them in robust, scalable systems. You'll collaborate closely with data engineers, product leads, backend engineers, and customer-facing teams to ensure that our AI systems deliver measurable value in real-world environments. As one of the earliest technical hires, you will help define our AI strategy, set technical standards, and establish best practices for applied AI at scale. responsibilities Develop and Deploy AI Systems Architect, build, and deploy ML/GenAI products on cloud infrastructure (AWS or similar). Design and implement end-to-end AI workflows: data ingestion, feature engineering, modeling, evaluation, and deployment. Create automated pipelines for continuous learning, model promotion, and performance monitoring. System Architecture & Reliability Lead the design of ML orchestration frameworks (Airflow, Kedro, ZenML, Flyte) to ensure reproducibility and scalability. Oversee deployment of large-scale and multi-agent AI systems with high reliability and fault tolerance. Continuously optimize workflows for efficiency, robustness, and performance in production. Applied Data Science & Business Impact Translate complex business problems into AI solutions, including data collection, experiment design, and roadmap planning. Develop interpretable, modular, and scalable ML systems that deliver measurable business value. Work directly with customers and stakeholders to ensure deployed systems achieve their intended impact. Innovation & Thought Leadership Stay current with advancements in AI/ML, including LLMs, diffusion models, graph AI, and agent architectures. Propose and prototype new approaches for integrating emerging technologies into production products. Develop methods to quantify and communicate AI performance and business ROI. Promote responsible, ethical, and impactful AI practices across the organization. all about you Proven track record of launching AI/ML products into production. Experience with core ML/AI tools: Python, PyTorch, TensorFlow / Keras, scikit-learn, SQL, Spark. Experience writing production-grade Python (object- and function-oriented). Hands-on expertise with large-scale ML systems, GenAI (LLMs, diffusion), agents, and graph-based models. Experience designing and managing ML orchestration workflows and versioned pipelines (Airflow, ZenML, Kedro, dbt, etc.). Strong problem-solving skills, adaptability, and a “hacker” mentality. Excellent communication skills-able to work with both technical and non-technical stakeholders. Demonstrated thought leadership and innovation in applied AI. benefits & perks Check out our one pager! location Hybrid role based in New York City; open to remote U.S. candidates willing to travel monthly to our NYC office. interview rounds Phone Screen Peer Interview Founders' Interview equal opportunity employer We are an equal opportunity employer and consider applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disability, veteran status, or any other characteristic protected by law. We actively encourage diversity, inclusion, and equitable hiring practices. If you require accommodations during the hiring process, please reach out to our recruitment team at **************

Deeptune builds training gyms for AI agents. We work with frontier AI labs to help them train the next generation of agentic models. We're backed by world-class investors and are closing our Series A in the coming weeks, have a world-class founding team, and have crossed $10M ARR in the last six months, with plans to 10x in 2026. training gym n /ˈtreɪnɪŋ dʒɪm/ A simulation environment where AI can practice doing tasks (like coding or making a spreadsheet) so it can learn and get better over time. About you You're a strong developer across backend and infrastructure (Python, Go, TypeScript, etc.) with a deep interest in agentic AI. We care more about what you've done, not how long you've been doing it. You've been a founding engineer, founded your own company, or had a major impact at a top-tier company, and you're ready to join an early-stage team. You are motivated by ownership, impact, and building frontier tech. Your work is a craft you want to master. You thrive in ambiguity and love hard problems. You appreciate diverse perspectives and uncommon ideas. You are excited about building in-person, 5 days a week, from our office in Union Square NYC. We encourage you to apply even if you don't perfectly match this description, but believe you would be a great fit. Comp & Equity: $200K-300K base Very strong equity Benefits 100% paid medical and dental coverage Professional development budget Daily team lunches Commuter benefits Unlimited PTO Interview process Reach out and let us know why you're interested Intro call with Tim, our founder Meet with a member of technical staff Join us onsite for a technical interview Offer

Anterior is on a mission to transform healthcare administration, making it seamless and invisible so clinicians can focus on delivering care. We've built an AI-powered platform designed by clinicians, for clinicians, to simplify administrative workflows and improve patient outcomes. By combining clinical expertise with cutting-edge technology, we're revolutionizing healthcare operations with responsible AI. We're growing rapidly and are backed by world-class investors including Sequoia, New Enterprise Associates (NEA), and Neo along with notable angels including the founders of DeepMind, Google AI, and Inflection AI. You can learn more about us here. Anterior is improving the experience of healthcare for everyone. We're working on the cutting edge of using technology to make clinical decisioning frictionless. We're building exciting tech for huge customers and we trust in the foundations: keep it simple, build strong foundations and the rest will follow. The Team: At Anterior, engineers share a strong "sense of product" and solve meaningful problems that simplify healthcare workflows. We collaborate in multidisciplinary teams to deliver secure, scalable, and user-focused solutions guided by best practices and modular design. We value diverse experiences and skill sets, continually expanding our team to tackle modern healthcare's challenges with creativity and precision. About You You have a passion for doing things The Right Way, you believe Less is More, you want to focus on foundations of system design and architecture (pacelc, consistency guarantees), you care as much about the code you do not write, you're tired of the hype treadmill and care about the fundamentals. You have battle scars from overengineered and underperforming slop, and you care about writing code that lasts. We're hiring from infra to frontend, there is room all the way up and down the stack. Come share your proudest firefighting story with us in an interview, bring your GitHub, and let's see if we're a good fit. If you're a junior passionate about coding and hacking: it's always ok to apply, shoot us a link to some of your work and let's talk anyway Tech Langs: Python / Go / TS, React (and HTMX if you can help!) Infra: Nix, CDKTF, AWS What's in it for you This is an opportunity to join the formative stages of a company that is working with cutting-edge technology to have a meaningful impact in healthcare. We're at an exciting inflection point, and you will be working with a world-class team, will hold significant responsibility, and will be given the opportunity to learn and grow rapidly. We take pride in our strong apprenticeship and coaching culture. We expect our early hires to become leaders both within our company and across the industry. You'll be given a lot of responsibility and and the opportunity for rapid growth. Benefits: Early-Stage Equity Competitive, top-of-market salary 100% covered health, dental, and vision insurance Catered lunches and a stocked kitchen Commuter benefits Company Laptop along w/ tools you need to succeed Learning & development budget Team-building events Flexible PTO

Our open-source Agent Platform is uniquely designed to make it easy for both engineers and non-technical teams to build agents on a single platform. Our customers include leading AI companies like Anthropic and Midjourney use our platform to build best-in-class AI experiences for their users and automate workflows for their teams. We're backed by Khosla Ventures and Y Combinator, growing quickly, and looking for exceptional engineers who want to work at the forefront of AI with a high-velocity team and are excited by open-source and TypeScript. About the role As a Staff Engineer, you'll own a large surface area of the product, both by being a product and system architect that's helpful to others on the team, as well as being a core individual contributor. You'll have significant ownership over how thousands of developers build AI agents, from API design to SDK ergonomics to the abstractions that make agentic systems easy to build. This is a high-leverage role where you'll: Own platform features end-to-end: architect, build, and maintain critical systems that our customers depend on. Lead technical and team direction: Serve as a leader and resource Shape the developer experience: design APIs, SDKs, and tools that developers love to use Build at the frontier and in public: work on cutting-edge agentic systems and see your work used in production at leading AI companies -- all while contributing to open source. Influence product direction: your technical and product insights will directly shape our roadmap Work directly with customers: understand how teams build AI agents and design elegant solutions for their needs What we're looking for Strong TypeScript expertise: 4+ years building full-stack products with TypeScript, with a deep understanding of end-to-end web fundamentals System design skills: you can architect APIs and systems that are elegant, scalable, and developer-friendly Product thinking: you care about the end-user experience and think through how people will actually use what you build Full-stack fluency: comfortable working across the stack, from APIs to SDKs to UIs High ownership: you want to own problems end-to-end, not just ship code Bonus points for Experience building with AI (prompts, evals, RAG, agentic workflows, etc.) Background in developer tools or B2B SaaS products Open source contributions or public projects that demonstrate your craft UX or design sensibility Our craft-driven culture We expect every engineer to have strong product intuition and to think through the complete user experience. If you love building for other developers and are excited about building end-to-end agentic systems, this role is a great fit. Why join us High impact: shape the platform that powers AI agents for leading companies Technical depth: work on complex, challenging problems at the frontier of AI Ownership: drive product, architectural, and technical decisions end-to-end Learning: get deep on how AI Agents work and what it takes to ship them in production

About Basis Basis equips accountants with a team of AI agents to take on real workflows. We have hit product-market fit, have more demand than we can meet, and just raised $34m to scale at a speed that meets this moment. Built in New York City. Read more about Basis here. About the Team We build the ML systems that power Basis's AI Accountant. Our systems read documents, reason over context, and complete real accounting workflows safely and accurately. We focus on the whole system, not just the model. We optimize everything around it: tools, memory, retrieval, orchestration, and evaluation. We push model providers to their limits when needed (custom runtimes, unusual packages, unconventional loops) and run experiments to learn quickly. We work in small, focused pods alongside Platform, Product, and Accounting experts. We think in systems, debate trade-offs, and write code that's observable, understandable, and built for continuous learning in production. About the Role As an ML Engineer at Basis, you'll own end-to-end projects that bring intelligence into production. You'll be the Responsible Party (RP) for systems that help our agents reason, plan, and evaluate themselves. That means you'll scope, build, and deliver from first principles. You'll have full autonomy: plan your projects, define success, run experiments, and decide when your system is ready to ship. You'll move fast, instrument everything, and design for clarity. You'll build the scaffolding that lets models act safely and improve continuously. This is a role for engineers who want to be both researchers and builders: reasoning through problems, experimenting with solutions, and shipping systems that get smarter over time. What you'll be doing: Build and evolve our agent systems Design and iterate multi-agent architectures that automate real accounting workflows. Build in autonomy boundaries, tool usage, and fallback behaviors that make agents safe and reliable. Manage context and memory for coherence across steps. Plan and execute agent loops with measurable success criteria. Route, evaluate, and optimize models under real-world constraints (latency, cost, accuracy). Design evaluation and experimentation frameworks Build scalable evaluation pipelines (offline and online) that run hundreds of experiments automatically. Define golden tasks, labeling strategies, and metrics that make performance measurable and comparable. Instrument the stack to detect regressions, track error patterns, and drive continuous improvement. Use data and experiments to drive product and architectural decisions, not just intuition. Engineer for context and retrieval Build prompt stacks and instruction hierarchies that structure model reasoning. Create retrieval and indexing pipelines that surface relevant context efficiently. Parse messy documents into structured representations that agents can understand. Design guardrails and validation layers to keep behavior safe and predictable. Operate as an RP: plan, build, deliver Scope your projects clearly. Write concise specs and architecture docs that eliminate ambiguity. Build, test, and instrument your systems end-to-end. Communicate progress clearly: what's built, what's learned, what's next. Work closely with your pod, teaching, unblocking, and sharing learnings as you go. 📍 Location: NYC, Flatiron office. In-person team. What Success looks like in this role You scope, execute, and deliver your systems from concept to production. You instrument everything, measure outcomes, and learn from data. You design clean abstractions for complex ML systems that others can build on. Your work makes the whole team faster and better through clear interfaces and insights. You move fast, stay curious, and build with conviction and care. Why Join Basis? We offer a competitive and thoughtful benefits package designed to support your physical, mental, and financial well-being: Health & Wellness: Premium Medical, Dental, and Vision coverage; Life Insurance; and 6 coaching & 6 therapy sessions through Spring Health. Flexibility: Unlimited PTO + 12 paid company holidays. In-Office Perks: Daily meal stipends, a fully stocked kitchen, and $300 toward your custom desk setup. Financial Benefits: Pre-tax commuter benefits and 401(k) retirement plan Team Culture: Monthly office activities and frequent optional team happy hours.

Applied AI Engineer Valthos Inc. Valthos is an applied biological intelligence company. We build and deploy software and biological AI systems to safeguard humanity. The same AI architectures that enable self-driving cars, land rockets with precision, and deliver expert-level reasoning are beginning to be deployed in biological design. To stay ahead, we must advance our arsenal of tools to capture and design against real-time sensitivities in nature's evolving mutational landscape. We are a group of mission-driven software engineers from Palantir and applied biological ML engineers from MIT's Broad Institute and DeepMind making the latest advances in computational biology accessible in the real-world for federal and commercial use. We are seeking a highly skilled, data-centric AI Engineer to develop and apply state-of-the-art ML methods for assessing and responding to biological threats and for rapidly designing precision biologics. The Role Contribute to crafting and executing on the Valthos-wide research and development roadmap Develop, build, and apply modeling approaches-including adapting and post-training biological frontier models-for tasks in biological security and the design of precision biologics Develop, build, and apply evaluation frameworks to rigorously assess model performance on key tasks Interrogate models to understand their biological learnings, capabilities, and limitations Collaborate closely with computational biologists to understand the signal and artifacts inherent in biological data, and to create and curate datasets Collaborate closely with software engineers to build, deploy, and scale model training and evaluation infrastructure Visualize and communicate results within Valthos and externally Work with customers and external collaborators to understand their needs and be an effective representative of Valthos Embrace learning about areas-technical and non-technical-across Valthos Stay up-to-date on the state-of-the-art methods at the intersection of AI and biology Qualifications (required) Experience with data-centric development and evaluation of ML models Highly proficient in Python and deep learning libraries (e.g., PyTorch) Experience with cloud computing platforms (e.g., AWS) and distributed systems Strong understanding of probability and statistics Qualifications (preferred) Proven ability to design, implement, and evaluate new ideas in ML Experience with pre- or post-training language models, developing reasoning agents, and/or time series modeling Experience working with biological data or other types of noisy and heterogenous datasets Experience with ML-centric bioinformatics and structure-based tools (e.g., AlphaFold) Experience building data pipelining and training infrastructure Contributions to open-source projects If there is a fit, we'll schedule two technical interviews. The final step is an onsite in our office, where you'll work on a small project, discuss ideas, and work with the wider team.

About Uncharted/Udio Udio builds extraordinary AI experiences to empower musical artists and super fans. Pairing best-in-class AI models with groundbreaking partnerships across the music industry, Udio's mission is to champion musicians and expand how fans engage with their favorite music and artists. Udio is backed by leading lights from tech and music, including a16z, Redpoint, Hanwha, will.i.am, Steve Stoute, Kevin Wall, and many others. For more information, please visit udio.com. About the Role We are looking for a full-stack scientist to pioneer quantitative research efforts at Udio. You will build at the intersection of research, engineering and product, bridging disciplines by drawing on huge, one-of-a-kind proprietary datasets of music, metadata and user interactions/feedback. Working closely with the modeling team, product leadership and the music evaluation manager, you will apply your research toward pushing the frontier of music generation, setting a course through a bleeding-edge product category and unlocking new revenues for artists and experiences for fans. What You'll Do Design & own evaluation/optimization frameworks for frontier music models You'll dive deep under the hood of our music generation systems, applying computational & human resources to understand model capabilities and identify areas for growth. You'll build optimization loops and apply your findings to our pretraining, post-training and inference systems as applicable. Drive product & research roadmap You'll own our data roadmap end-to-end, formulating research questions, exploring/linking/expanding data sources and conducting experiments at your discretion. Your work will span data mining, machine learning, causal inference, survey design and more, and your results will be critical for decision-making in product development, research investment and overall business direction. Build stable infrastructure Your work will reach far beyond the jupyter kernel, manifesting in robust integrations with our research & product tech stacks, potentially in performance-critical paths. You'll also build large-scale standalone data processing systems, allocating resources as needed to manage the data ecosystem. Champion scientific rigor As our first quantitative researcher, you'll cultivate a culture of scientific rigor across the company and deepen common understanding of models, users and data. You'll proactively identify opportunities, define metrics, share results, and build a rigorous foundation upon which to understand our highly subjective domain. What We're Looking For Deep quantitative expertise: Ph.D. in statistics, mathematics, physics, or another quantitative discipline, or 5+ years' industry experience as a quantitative analyst / data scientist Autonomy & ownership: You thrive in greenfield research domains, undefined product categories and small, flat teams. Driven by curiosity and good taste, you ask good questions in addition to finding good answers. Engineering chops: You're adept in translating your ideas into clear, production-ready code and collaborating in an active research codebase. Excellence in scientific communication: You relate technical information with rigor and crystal clarity to researchers, engineers, product managers and business partners alike. Nice to Have Obsession with music & the science of sound. Experience in DSP, MIR, music production / composition / performance, and a big record collection all a huge plus. Familiarity with deep learning frameworks, especially JAX. Experience with GCP, Apache Beam/DataFlow, Kubernetes, TensorFlow Data / TFRecord. Experience designing evaluation frameworks specifically for generative model outputs in any modality. Why Join Us Work at the intersection of science & art with a bleeding-edge music ML ecosystem, one-of-a-kind proprietary datasets and a passionate userbase. Deploy substantial research compute resources as needed, including a powerful personal TPU pod. Join a small, ambitious team which highly values autonomy, interdisciplinarity and continual learning. Benefits Highly competitive salary and equity Quarterly productivity budget Flexible time off Productivity package, including ChatGPT Plus, Claude Code, and Copilot Top-notch private health, dental, and vision insurance for you and your dependents 401(k) plan options with 5% employer matching Concierge medical and primary care through One Medical and Rightway Mental health support from Spring Health Personalized life insurance, travel assistance, and many other perks Udio's success hinges on hiring great people and creating an environment where we can be happy, feel challenged, and do our best work. Udio provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability This role is eligible for a compensation package of base salary, equity, and benefits. The salary range for this role is $250k - $350k. Actual salary may vary based on level, work experience, performance, and other factors evaluated during the hiring process.

xAI's mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company's mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. Focus Creating and driving engineering agenda to toward superhuman multimodal capabilities, which include both multimodal understanding and multimodal generation, across different modalities including image, video and audio. Improving data quality, developing data filtering/generation techniques, and performing data study, on pretraining scale. Creating evaluation frameworks and internal benchmarks. Designing and implementing effective and efficient algorithms for achieving state-of-the-art model performance. Ideal Experience Hands-on experience on visual, audio or multimodal pretraining. Track record in leading engineering that significantly improves the capability and performance of neural networks, whether better data or better modeling. Experience in data-driven experiment designs and systematic analysis for iterative model debugging. Experience in developing or working with large-scale distributed machine learning systems. Ability to do whatever is necessary to deliver the best end-to-end user experience. Tech Stack Python Jax Rust Interview Process After submitting your application, the team reviews your CV and statement of exceptional work. If your application passes this stage, you will be invited to a 15 minute interview ("intro call") during which a member of our team will ask some basic questions. If you clear the initial , you will enter the main process, which consists of four technical interviews: One-on-one engineering discussion & coding interviews (three meetings total) Meet the Team: Present your past exceptional work and your vision with xAI to a small audience. Every application is reviewed by a member of our technical team. All interviews will be conducted via Google Meet. Location The role is based in the New York area. Candidates are expected to be located near the New York City area or open to relocation. Annual Salary Range $180,000 - $440,000 USD Benefits Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks. xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Member of Technical Staff - ML Engineering Note: This role is 100% on-site in NYC About the Company This fast-growing NYC-based AI startup is revolutionizing the accounting industry by building a team of AI agents that execute real-world accounting workflows. Founded in 2023 and headquartered in the Flatiron district, the company has already: Raised $34M from top-tier investors including leaders from the ML and fintech sectors. Achieved product-market fit with demand exceeding current capacity. Experienced 10x revenue growth in just the past 5 months. They operate on the cutting edge of what's technically possible, assembling top minds from ML, engineering, and accounting. Joining now means becoming an early member of a small, high-ownership team shaping the future of AI in enterprise systems. What You'll Do As a Member of Technical Staff on the World Modeling team, you will: Design and build the “world” that the company's AI agents interact with, modeling interconnected systems and abstractions. Develop frameworks and coding structures that enable AI agents to understand and navigate complex real-world workflows (e.g., accounting tasks). Define rules, constraints, and context in which AI agents operate. Collaborate with top engineers, ML researchers, and domain experts in an interdisciplinary team. Take ownership of projects end-to-end, from design to production deployment. Mentor and be mentored by other engineers as the team scales rapidly. Role Requirements Experience & Skills 4-8 years of experience building complex systems (Python preferred). Strong background in Machine Learning fundamentals, with a first-principles mindset. Deep experience modeling interconnected systems and reasoning about trade-offs and constraints. Previous experience as an early technical member at a fast-paced startup. Degree in Computer Science, Physics, Math, or Statistics (preferably from a top university). Attributes Intense curiosity and drive to solve hard, complex problems. Thrives in a high-ownership, high-speed startup environment. Eager to work in-person 5 days/week with a cross-disciplinary team. Dedicated to mentoring and collaboration. Compensation & Benefits Base Salary: $150K - $300K Equity: Highly competitive, well above market Comprehensive health, dental, and vision benefits Visa sponsorship available (all types) Opportunity to build on the cutting edge of AI alongside world-class colleagues Tech Stack Languages: Python (primary), with potential for other languages as needed Focus Areas: Machine Learning, agentic systems, large-scale system modeling, data infrastructure Interview Process Intro Call Initial Screen Technical Interview 1 Technical Interview 2 Onsite Interview (3-4 hours) Offer Hiring Number of Vacancies 5 positions available

About the Role A1 is building a proactive AI system that understands context across conversations, plans actions, and carries work forward over time. You will work on core ML systems under the guidance of senior engineers. This role is for builders who want to grow their judgment by shipping real ML systems in production. Focus Build and improve ML components across data, training, evaluation, and inference. Fine-tune and adapt models as part of larger production systems. Implement evaluation and testing to understand model behavior. Help build and maintain data pipelines for real-world and synthetic data. Debug model issues, performance problems, and production incidents. Ship improvements iteratively and learn from real user feedback. Work closely with senior ML engineers and product teams. Work under real production constraints: latency, cost, reliability, and safety Tech Stack Python PyTorch / JAX Production ML systems running on GPUs Ideal Experience Strong foundations in machine learning and modern neural architectures. Some hands-on experience training, fine-tuning, or deploying ML models. Comfortable writing production-quality code and learning new tools quickly. Curious, coachable, and eager to learn from real systems in production. Able to work through ambiguity with guidance and grow ownership over time. Bias toward shipping, iteration, and continuous improvement. How We Work Our organization is very flat and our team is small, highly motivated, and focused on engineering and product excellence. All members are expected to be hands-on and to contribute directly to the company's mission. Interview process If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

Who are we? Our mission is to scale intelligence to serve humanity. We're training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what's best for our customers. Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products. Join us on our mission and shape the future! Why this role? We're looking for an experienced machine learning researcher / engineer who can help us push the frontiers of agentic LLM systems. As a part of the team, you will help drive exploration and development of agentic techniques and have the opportunity to build the models that power our agentic solutions. Agentic LLM systems are being deployed widely across enterprise companies including through Cohere's North platform. In this role, you'll be working with a team developing new strategies for training models for advanced agent capabilities including reasoning, tool use, and memory. This includes developing data-generation techniques for post-training (SFT and RL*) Cohere's models. Model advancements have direct impacts on North and other Cohere products creating an exciting opportunity where core model development leads to direct product advancements. Please Note: We have offices in London, Toronto, San Francisco, and New York, but we also embrace being remote-friendly! Our preference for this role is that you are based in Eastern Time, New York office, remote or hybrid works! As a Member of Technical Staff for Agents Modeling you will: Design and develop novel agentic solutions Improve upon SOTA on hard agentic tasks Research the next-generation of on-line learning-from-experience self-improvement Work with partner teams (Reasoning, Post-training, Pre-training, etc.) to improve performance of agentic system Work with an amazing team of researchers and engineers pushing the boundaries You may be a good fit if you have: Have a PhD in computer science or related field or similar industry research experience Strong software engineering skills Proficiency in Python and experience with ML-related code (e.g., pytorch, numpy, etc.) Experience with LLMs and agentic frameworks Experience with post-training LLMs (SFT, PEFT, or RL*) Experience with building synthetic data generation pipelines If some of the above doesn't line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs. Full-Time Employees at Cohere enjoy these Perks: 🤝 An open and inclusive culture and work environment 🧑 💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks 🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months 🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement 🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend ✈️ 6 weeks of vacation (30 working days!)

About us ATG (Autonomous Technologies Group) is an AI lab deploying frontier reasoning systems within financial markets. Founders: Early GPU cloud (9 figure exit). Investors: Garry Tan / YC + Founder of one of the most successful quant funds, BoxGroup (Plaid, Ramp, Stripe), top-tier angels. About the Role You'll design and scale the compute, storage, and data infrastructure that powers advanced AI research. Your work will ensure the speed, reliability, and reproducibility of every experiment and deployment. Responsibilities Develop and maintain scalable compute infrastructure (cloud, bare metal, clusters). Automate build, test, and deploy pipelines for research and production. Build tools for experiment tracking, monitoring, and reproducibility. Ensure security, reliability, and rapid iteration across all environments. Requirements Deep experience with cloud-native platforms (AWS, GCP, OCI), containerization, and orchestration (Kubernetes, Docker). Strong proficiency in Python and infrastructure-as-code tools (Terraform, Ansible, etc.). Experience scaling infra for ML, data, or research workflows. Relentless focus on reliability, observability, and developer velocity. Expertise in leveraging the latest AI tools (Cursor, Claude Code, Codex, etc) to increase productivity & code output while maintaining high code quality, maintainability, and structure. Why Join ATG We're building a small, elite team. If you're excited by AI, markets, and building from first principles, we'd love to meet you. Work on AI with a massive market opportunity Early team of repeat founders backed by top investors High agency, talent dense, zero bureaucracy