Operations engineer jobs in South San Francisco, CA

It's fun to work in a company where people truly believe in what they're doing! At BlackLine, we're committed to bringing passion and customer focus to the business of enterprise applications. Since being founded in 2001, BlackLine has become a leading provider of cloud software that automates and controls the entire financial close process. Our vision is to modernize the finance and accounting function to enable greater operational effectiveness and agility, and we are committed to delivering innovative solutions and services to empower accounting and finance leaders around the world to achieve Modern Finance. Being a best-in-class SaaS Company, we understand that bringing in new ideas and innovative technology is mission critical. At BlackLine we are always working with new, cutting edge technology that encourages our teams to learn something new and expand their creativity and technical skillset that will accelerate their careers. Work, Play and Grow at BlackLine! The Principal AI/ML Operations Engineer leads the architecture, automation, and operationalization of both machine learning and AI systems at scale. This role defines the strategy and technical standards for ML-Ops and AIOps across the organization, ensuring models and agents are evaluated, deployed, governed, and monitored with reliability, efficiency, and compliance. The candidate will collaborate across AI, data, and product engineering teams to drive best practices for serving, observability, automated retraining, evaluation flywheels, and operational guardrails for AI systems in production You'll Get To: Leadership and Strategy Define enterprise-level standards and reference architectures for ML-Ops and AIOps systems. Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs). Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments. Lead incident response and reliability strategies for ML/AI systems. AI System Deployment and Integration: Lead the deployment of AI models and systems in various environments. Collaborate with development teams to integrate AI solutions into existing workflows and applications. Ensure seamless integration with different platforms and technologies. Define and manage MCP Registry for agentic component onboarding, lifecycle versioning, and dependency governance. Build CI/CD pipelines automating LLM agent deployment, policy validation, and prompt evaluation of workflows. Develop and operationalize experimentation frameworks for agent evaluations, scenario regression, and performance analytics. Implement logging, metering, and auditing for agent behavior, function calls, and compliance alignment. Create scalable observability systems-tracking conversation outcomes, factual accuracy, latency, escalation patterns, and safety events. Architect end-to-end guardrails for AI agents including prompt injection protection, identity-aware routing, and tool usage authorization. Collaborate cross-functionally to standardize authentication, authorization, and session governance for multi-agent runtimes. Model Deployment and Integration: Architect and standardize model registries and feature stores to support version tracking, lineage, and reproducibility across environments. Lead the deployment of machine learning models into production environments, ensuring scalability, reliability, and efficiency. Collaborate with software engineers to integrate machine learning models into existing applications and systems. Implement and maintain APIs for model inference. Infrastructure and Environment Management: Design and manage training infrastructure including distributed training orchestration, GPU/TPU resource allocation, and automatic scaling. Implement CI/CD for model workflows using pipelines integrated with model validation, bias checks, and rollback automation. Build standardized experimentation frameworks for reproducible training, tuning, and deployment cycles (MLflow, W&B, Kubeflow). Manage and optimize the infrastructure required for machine learning operations in cloud. Work closely with other teams to ensure the availability, security, and performance of machine learning systems. Monitoring and Maintenance: Implement robust monitoring solutions for deployed machine learning models to detect issues and ensure performance. Collaborate with data scientists and engineers to address and resolve model performance and data quality issues. Conduct regular system maintenance, updates, and optimizations to ensure optimal performance of machine learning solutions. Automation and Orchestration: Develop and maintain automation scripts and tools for managing machine learning workflows. Implement orchestration systems to streamline the end-to-end machine learning lifecycle, from data preparation to model deployment. Collaboration with Data Science Teams: Collaborate with data scientists to understand model requirements and constraints for deployment. Facilitate the transition of machine learning models from research to production, ensuring scalability and efficiency. Performance Optimization: Identify and implement optimizations to enhance the performance and efficiency of machine learning models in production. Conduct performance analysis and implement improvements based on resource utilization of metrics. Security and Compliance: Implement security measures to protect machine learning systems and data. Ensure compliance with regulatory requirements and industry standards related to machine learning and data privacy. Integrate audit controls, metadata storage, and lineage tracking across ML and AI workflows. Ensure complete monitoring and feedback loops including event logs, evaluations, and automated retraining triggers. Enforce secure deployment patterns with Infrastructure-as-Code and cloud-native secrets management. Define SLAs, error budgets, and compliance reporting mechanisms for ML and AI systems. What You'll Bring: Education and Experience: Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. 10+ years in ML infrastructure, DevOps, and software system architecture; 4+ years in leading MLOps or AI Ops platforms. Technical Skills: Strong programming skills in languages such as Python, Java, or Scala. Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow). Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure). Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management. Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation. Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking. Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads. Proficiency in containerization technologies (e.g., Docker, Kubernetes). Operations and Infrastructure: Proficient in scripting languages (e.g., Bash, python) for automation. Experience with workflow orchestration tools (e.g., Apache Airflow). Expertise in managing and optimizing cloud-based infrastructure. Familiarity with DevOps practices and tools for automated deployment. Understanding of network configurations and security protocols. Problem-solving and Critical Thinking: Ability to define problems, collect and analyze data, and propose innovative solutions. Strong critical thinking skills to evaluate models, identify limitations, and Adaptability and Learning Agility: Comfortable working in a fast-paced, rapidly evolving environment. Proactive in staying up to date with the latest trends, techniques, and technologies in AI/data science Thrive at BlackLine Because You Are Joining: A technology-based company with a sense of adventure and a vision for the future. Every door at BlackLine is open. Just bring your brains, your problem-solving skills, and be part of a winning team at the world's most trusted name in Finance Automation! A culture that is kind, open, and accepting. It's a place where people can embrace what makes them unique, and the mix of cultural backgrounds and varying interests cultivates diverse thought and perspectives. A culture where BlackLiner's continued growth and learning is empowered. BlackLine offers a wide variety of professional development seminars and inclusive affinity groups to celebrate and support our diversity. BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws. BlackLine recognizes that the ways we work and the workplace itself have shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 2 days a week.

Machine Learning Engineer/Researcher Salary: Up to $300k Base The Role First hire owning agentic video pipelines. Build routing, fine-tuning, and backend logic that powers a next-gen video co-pilot. High autonomy. No hand-holding. What You'll Own Agentic pipelines for video/image tasks Routing across open-source + external VLM/LLM providers Fine-tuning + post-training on targeted tasks Low-latency backend services for video understanding Turning product needs into shipped features Must-Haves 2+ years fine-tuning LLMs/VLMs Hands-on with video/image models Built agentic or multimodal applications Comfortable as the only specialist building the foundation

Senior Machine Learning Engineer (LLM / Audio / Voice AI) $200,000-$300,000 + Equity San Francisco Bay Area (Relocation + Sponsorship Available for Exceptional Talent) Permanent Our client is a rapidly scaling AI startup operating at $1M+ ARR per employee, building the next generation of real-time voice automation. They're now hiring exceptionally talented (Doesn't matter the years of experience) ML Engineer to help push the boundaries of speech, audio, and LLM-driven systems. This role sits at the core of their product: Training LLMs and audio models Designing high-performance ML infrastructure Deploying models that must operate reliably under real-world, latency-sensitive conditions Work end-to-end - experimentation, evaluation, productionisation, and continuous improvement The environment is fast-paced, deeply technical, and highly collaborative, with 80%+ onsite time expected. This is a true startup role: long hours, high ownership and reward, fast iteration, and the chance to make outsized impact on a rapidly growing product used by hundreds of thousands of customers. They're looking for engineers with strong academic foundations and demonstrated technical excellence (advanced degrees or standout research/engineering experience), plus hands-on experience shipping ML systems in demanding environments. If you thrive in ambiguity, love building real-world AI systems, and want to help shape a high-velocity ML organisation from the ground up, this is the opportunity. Apply now or reach out for details or to explore the role confidentially.

📍 Hayward, CA (On-site; occasional visits to Fremont, CA) 🕒 Contract: 6-12 months 💲 $75-85/hour 🏭 Industry: Autonomous Mobility About the Role We're seeking an experienced SAP Operations Support Engineer to support and enhance SAP systems and operational tools for Base Operations, with occasional support for General Assembly. This role focuses on SAP S/4HANA data integrity, system configuration, process improvement, and cross-functional collaboration to improve operational efficiency across vehicle operations. The ideal candidate is highly detail-oriented, self-driven, and comfortable working in fast-paced, complex environments. You enjoy solving system, data, and process challenges and can communicate effectively with both technical and non-technical partners. Key Responsibilities SAP Support & Data Management Act as the SAP data steward, maintaining vehicle lists, work centers, measuring points, counters, maintenance plans, task lists, catalog codes, and equipment structures. Partner with Business Applications teams to resolve data inaccuracies and support As-Maintained BOM cleanup. Provide SAP configuration management support for Base Operations ahead of major milestones. Identify and lead SAP product improvements and automation initiatives. Evaluate SAP user experience and drive enhancements to improve usability and adoption. Serve as the primary SAP subject-matter expert, providing troubleshooting, maintenance, and ongoing system support. Collaborate with training teams to develop role- and module-specific SAP training for BaseOps users. Systems, Infrastructure & IT Application Support Provide IT application support for critical Base Operations systems and act as a liaison with Corporate IT. Lead infrastructure and application improvement projects based on data insights and user feedback. Support technical publications and service manual authoring tools, release software, and customer-facing documentation systems. Partner with documentation teams to improve documentation review and release processes. Support development and use of analytics tools, dashboards, and reporting frameworks. Lead data auditing and compliance efforts to ensure accuracy, governance, and system reliability. Communicate project status, milestones, and outcomes to internal and external stakeholders. What You'll Work On Daily Collaborate closely with Business Applications on SAP data accuracy and system improvement initiatives. Work cross-functionally with Program Management, Strategic Operations, Data Science, Fleet Support, and Engineering teams. Monitor and support critical BaseOps systems and assets, including troubleshooting and maintenance. Support software and hardware rollouts, user training, and system infrastructure planning. Contribute to projects involving SAP S/4HANA, SAP MES, and related IT systems that improve system efficiency and operational uptime. Occasionally support website maintenance, operational analytics databases, dashboards, and vehicle production line systems. Qualifications Bachelor's degree in Information Technology, Engineering, or equivalent experience. 6-8 years of experience in a systems operations or IT support role. Hands-on experience with SAP S/4HANA. Strong verbal and written communication skills. Highly self-motivated, detail-oriented, and able to manage competing priorities. Experience with UI development and maintenance, including UX studies. Coding experience with HTML, CSS, and JavaScript. Broad IT systems knowledge and operational awareness. Nice to Have Experience with SAP ME/MII. Familiarity with Jira, Confluence, or similar ticketing/documentation tools. Experience with web development tools (e.g., Oxygen). Experience building dashboards and data analytics tools. Prior systems support experience in production environments or vehicle fleets. Interview Process 30-minute Zoom interview with the Hiring Manager 1-1.5 hour panel interview with the technical team

Lead Machine Learning Engineer - Generative AI for the Physical World A rare opportunity has emerged for a visionary Lead Machine Learning Engineer to build the core intelligence for a stealth-mode, well-funded AI company. This foundational leadership role is for someone passionate about teaching machines to understand and engineer the physical world, moving beyond language and into the complex domain of 3D geometry and physics. Why Join? This is a chance to define a new category of software from the ground up. You will have the autonomy to set the technical vision, build a world-class team, and solve fundamental AI challenges that directly impact how next-generation products are designed and built. You will be instrumental in creating the "brain" that powers a revolutionary platform. The Company My client is a pioneering startup developing a new class of generative AI. Their platform uses autonomous agents to design, test, and optimize complex physical systems, aiming to radically accelerate today's slow and manual engineering cycles. Backed by top-tier investors, the company is positioned to become a leader in the application of AI to advanced hardware design and manufacturing. The Role As the Lead Machine Learning Engineer, you will architect the company's entire ML strategy. You will lead the research and development of the core models that allow AI agents to perceive and reason about 3D geometry. Your primary focus will be on defining the technical roadmap, hiring and mentoring a high-performing team, and guiding the development of novel techniques in geometric deep learning and multimodal reasoning. The Essential Requirements Proven experience leading machine learning teams, setting technical direction, and mentoring senior engineers. Deep expertise in 3D perception, scene understanding, or geometric deep learning (e.g., from robotics, AV, AR/VR). A strong track record of architecting and deploying complex ML systems from research to production. Fluency with modern ML frameworks (e.g., PyTorch) and models for geometric data (GNNs, 3D CNNs, NeRFs). Ability to translate ambiguous product goals into a concrete technical roadmap and execute effectively. What Will Make You Stand Out A PhD in a relevant field such as Computer Science or Robotics. A background in mechanical, aerospace, or a related engineering discipline. Experience integrating perception models with LLMs or other agent-based systems. A history of publications in top-tier machine learning conferences. Benefits Up to $260,000 base Meaningful equity A key leadership role with the autonomy to shape the company's technical culture and direction. The opportunity to solve high-impact problems at the intersection of AI and engineering. If you are interested in this role, please apply with your resume through this site. SEO Keywords for Search Head of Machine Learning, Head of AI, AI Lead, ML Lead, Principal ML Engineer, Machine Learning Manager, AI Research Lead, 3D Perception, Geometric Deep Learning, Computer Vision, GNN, Graph Neural Networks, 3D Transformers, NeRF, Point Clouds, CAD, Generative AI, Autonomous Agents, Robotics, PyTorch, MLOps, LLM, Reinforcement Learning, AI for Engineering, Simulation, Computational Geometry. Disclaimer Attis Global Ltd is an equal opportunities employer. No terminology in this advert is intended to discriminate on any of the grounds protected by law, and all qualified applicants will receive consideration for employment without regard to age, sex, race, national origin, religion or belief, disability, pregnancy and maternity, marital status, political affiliation, socio-economic status, sexual orientation, gender, gender identity and expression, and/or gender reassignment. M/F/D/V. We operate as a staffing agency and employment business. More information can be found at attisglobal.com.

Machine Learning Engineer - Applied AI Systems San Francisco, CA - On-site $170k-$250k + equity A venture-backed AI company is expanding its engineering group and looking for a Machine Learning Engineer to help push forward a new generation of decision-support products used in complex, data-heavy environments. The team builds systems that analyse large, unstructured datasets and surface insights that help organisations make high-stakes choices more consistently. You'll join a small group of engineers and researchers working on applied ML problems that combine pattern recognition, anomaly detection, language modelling and real-time data interpretation. This is a hands-on engineering role where you'll prototype, train, evaluate and productionise models that directly shape the product experience. What you'll work on Designing and implementing ML pipelines for processing a wide variety of semi-structured inputs. Training and adapting large language models to handle classification, extraction and reasoning tasks. Developing methods to identify irregularities, inconsistencies and unusual patterns within customer-supplied data. Improving the performance, latency and reliability of deployed models at scale. Collaborating with software engineers to integrate new capabilities into customer-facing features. Exploring new approaches in multimodal modelling, retrieval-augmented generation and adaptive learning systems. Who you might be Someone with professional experience in ML engineering, data science, applied research or similar. Confident programming in Python and fluent with at least one modern deep learning toolkit. Comfortable working with messy, real-world data rather than clean academic datasets. Experience with information extraction, language models, anomaly detection or data quality modelling is valuable. Interested in joining a company where the ML team has genuine influence over product direction. Enjoys experimentation, iteration and solving problems that don't have an obvious starting point. (No strict requirement on years - strength of experience matters more than time served.) Why this is different You'll work on technically challenging problems where accuracy genuinely matters. The company is scaling quickly and investing heavily in expanding its AI group. You'll collaborate closely with product and engineering leadership, not sit in a research silo. The environment is fast-moving, with opportunities to own projects end-to-end. Generous salary, equity and benefits package. Location & Work Style On-site in San Francisco to support a highly collaborative engineering culture. Hybrid flexibility may be available for senior hires already living in the Bay Area.

Source One is a consulting services company and we're currently looking for the following individual to work as an on-site consultant to an autonomous vehicle (AV) ride-sharing company in Hayward, CA. Title: SAP Operation Support Engineer (Contract) Pay Rate: $87.25/hr (W-2) Summary: Our client is seeking an SAP Operation Support Engineer to support SAP S/4, key Base Operations systems, and broader IT infrastructure initiatives. This role focuses on SAP data accuracy, system configuration, operational improvements, and cross-functional collaboration to enhance vehicle and production operations. You will also assist with analytics tools, documentation systems, and general IT application support. The ideal candidate is detail-oriented, proactive, and experienced in SAP S/4 and system operations, with strong communication skills and the ability to manage complex data and processes in a fast-paced environment. Key Responsibilities : SAP Support & Data Management - Serve as the SAP data steward: maintain vehicle lists, equipment structures, work centers, measuring points, counters, task lists, maintenance plans, and catalog codes. - Partner with the Business Applications team on As-Maintained BOM cleanup and resolving data inaccuracies. - Provide configuration management support in SAP for Base Operations ahead of key milestones. - Lead SAP improvement and automation initiatives and evaluate user experience to drive usability enhancements. - Act as the primary SAP subject-matter expert, handling troubleshooting, maintenance, and user support. - Work with internal training teams to create module-specific SAP training for BaseOps users. Systems, Infrastructure & IT Application Support - Provide general IT application support for Base Operations systems and advocate operational needs with Corporate IT. - Lead IT infrastructure and application improvement projects informed by data insights and user feedback. - Support development, maintenance, and operations of technical publications tools, release software, and customer-facing documentation systems. - Improve documentation review workflows in partnership with the BaseOps documentation team. - Support development and use of analytics tools, dashboards, and reporting frameworks to improve operational efficiency. - Conduct data auditing and compliance activities to ensure accuracy, governance, and system reliability. - Communicate project progress, milestones, and outcomes to internal and external partners. Daily Focus : - Manage SAP data accuracy and system improvement projects in close collaboration with Business Applications, Program Management, Strategic Operations, Data Science, Fleet Support, and Engineering. - Monitor and support BaseOps systems and infrastructure, lead software/hardware rollouts, deliver training, troubleshoot issues, and contribute to overall system architecture. - Provide support for SAP S/4, SAP MES, and other IT systems; contribute to operational tools and processes that improve fleet and production uptime. - As needed, support website development and maintenance of operational databases and dashboards. Qualifications : - B.S. in Information Technology or an equivalent engineering field - 6-8 years of experience in a System Operations Support role - Hands-on experience with SAP S/4 - Strong written and verbal communication skills - Highly self-motivated, detail-oriented, and able to prioritize multiple assignments - Experience with UI development/maintenance and UX studies - Coding experience: HTML, CSS, JavaScript Bonus Qualifications : - Experience with SAP ME/MII - Familiarity with Jira/Confluence or similar tools - Experience with web development tools (e.g., Oxygen) and building analytics dashboards - Prior support experience in production or vehicle fleet environments

Job Title: NPI Mechanical Engineer Job Type: Full-time Work Schedule: Onsite Salary: $88000 - 120000/Yearly The Mechanical Engineer (Level 2) works with local manufacturing teams and Taiwan-based design teams to resolve mechanical issues in a timely manner and ensure smooth product development and production support. This role supports new product introduction (NPI), fixture and component design, and continuous improvements in manufacturability and assembly. This position is part of the Engineering Services team, which works across departments to support the engineering and operation teams with technical expertise in electronics, operational software, and systems integration. Responsibilities: Collaborate with cross-functional teams including R&D, manufacturing, and customer support. Analyze and resolve mechanical engineering issues, coordinating with design teams to determine root causes. Manage and guide the transition of NPI products into production, ensuring manufacturability and assembly readiness. Design and validate testing fixtures, jigs, and mechanical components to support new projects and production needs. Provide design-for-manufacturability (DFM) and design-for-assembly (DFA) feedback to improve product quality and efficiency. Review mechanical drawings and specifications for accuracy, tolerance, and compliance with company standards. Perform mechanical stress, fit, and tolerance analyses to ensure reliability and performance. Conduct failure analysis and propose corrective actions for mechanical and structural issues. Support tooling, sheet metal, and plastic component design, fabrication, and inspection. Document and update SOPs (Standard Operating Procedures), work instructions, and test plans. Support factory teams in the U.S. by bridging communication between Taiwan design teams and local production teams. Participate in cost reduction and process improvement initiatives related to mechanical design and manufacturing. Qualifications: Knowledge and experience with server, storage, and/or PC products. Familiarity with creating server assembly standard operating procedures (SOPs) for production lines. Skill in using measuring tools such as calipers and altimeters. Ability to interpret engineering drawings, including dimensional tolerances and GD&T (Geometric Dimensioning & Tolerancing). Understanding sheet metal product production and inspection; familiarity with NCT and hard tooling manufacturing is desirable. Understanding of plastic part production and inspection; familiarity with mold-up and hard tooling processes is desirable. Strong analytical problem-solving and communication skills. Proficiency in CAD tools (e.g., Creo/Pro-E) preferred. Bachelor's or Master's degree in Mechanical Engineering or equivalent. Minimum of 3 years of professional mechanical engineering experience. Ability to walk and stand on cement floors for extended periods. Ability to stoop, bend, and perform repetitive tasks. Prolonged periods of sitting and computer work. Ability to lift up to 30 pounds. About Maxonic: Since 2002 Maxonic has been at the forefront of connecting candidate strengths to client challenges. Our award winning, dedicated team of recruiting professionals are specialized by technology, are great listeners, and will seek to find a position that meets the long-term career needs of our candidates. We take pride in the over 10,000 candidates that we have placed, and the repeat business that we earn from our satisfied clients. Interested in Applying? Please apply with your most current resume. Feel free to contact Pramod Kumar (******************** / *************** for more details.

80Twenty is a boutique marketing recruitment agency that connects high-growth companies with exceptional candidates. Want to build technology that truly moves the needle in healthcare? Join a fast-scaling, profitable healthcare services company - independently grown and not VC-backed - on a mission to make healthcare simpler, smarter, and more human! Our client is a healthcare tech and services company based in San Francisco, combining clinical expertise, operational excellence, and modern engineering to reshape how people experience care. From personalized medication management and transparent pharmacy pricing to community-based chronic care support, we're building a system that empowers both patients and providers. This is a fully onsite role based in San Francisco, CA. Candidates must be located within 30 miles of San Francisco. The standard schedule is Monday-Friday, 9am-7pm and may vary depending on business needs and role responsibilities. In this role, you will: Design, build, and scale backend services that power pharmacy, telehealth, and patient-facing workflows. Collaborate cross-functionally with product, operations, and pharmacy teams to deliver seamless integrations and reliable systems. Lead architectural design discussions and set long-term technical direction for the backend stack. Implement best practices for system reliability, observability, security, and scalability. Drive operational excellence through CI/CD pipelines, cloud infrastructure (AWS), and container orchestration (Kubernetes). Mentor fellow engineers and help shape our backend engineering culture. Optimize system performance and streamline complex data flows across distributed services. Influence and define standards for how we build, test, and deploy software across the company. Who You Are 7+ years of backend engineering experience, ideally in fast-moving production environments. Strong experience with Node.js (TypeScript / JavaScript) and modern backend frameworks. Deep familiarity with AWS, Kubernetes, CI/CD, and distributed system design. Adept at owning code from design through deployment - you care about maintainability, reliability, and long-term scalability. Excellent communicator who enjoys collaborating across disciplines. Motivated by solving complex real-world problems in healthcare and improving patient outcomes. Bonus points for experience in healthcare, pharmacy systems, inventory/fulfillment flows, or regulated environments. Why This Role Stands Out You'll own high-impact systems that directly affect patient and provider experiences. You'll shape backend architecture and engineering best practices in a growing company. You'll join a profitable, non-VC-backed organization focused on long-term sustainability. You'll work in-person with an ambitious, mission-driven team in downtown San Francisco. Competitive compensation, equity opportunities, and strong benefits designed to help you thrive. This is a great opportunity to be a key member of the engineering team, taking technical ownership of our pharmacy platform's core backend systems. Your work will directly power real-time healthcare operations and improve access to care. If you're excited to apply your engineering expertise to meaningful healthcare infrastructure - and want to join a company that values autonomy, sustainability, and impact - we want to hear from you! Base salary: $250k-300k DOE + generous equity and benefits

Mechanical Engineer (Robotics) We are partnering with a robotics company building complex electro-mechanical systems where mechanical design directly determines real-world performance. This role is for someone who doesn't just design parts, but owns motion, reliability, and scale. What You'll Do Own the end-to-end mechanical design of complex electro-mechanical systems with moving parts Design and prototype custom mechanisms and actuators under aggressive timelines Drive concepts from first prototype through high-volume production Personally design parts for volume manufacturing processes, including: Injection molding Die casting Stamping / sheet metal Extrusion Powder metal / MIM Partner closely with contract manufacturers (CMs) to ensure DFM, reliability, and cost targets are met Build systems that are not just elegant but robust, testable, and shippable at scale What We're Looking For Exceptionally strong mechanical intuition, you understand how things move, fail, and improve Proven ability to design and prototype quickly without sacrificing rigor Track record of shipping reliable, hardware products at scale Deep hands-on experience designing custom mechanisms, joints, transmissions, and actuators Experience owning mechanical architecture for complex systems with dynamic loads and tight tolerances Comfortable operating across ambiguity, tight timelines, and high expectations Required Background Currently working at a robotics company (hands-on mechanical role) Background in electro-mechanical systems with real moving parts (not CAD-only work) Experience taking designs from concept → prototype → volume production Ideal Signals Designed robotic arms, legs, mobile platforms, end-effectors, or actuation systems Personally responsible for motor selection, gearing, kinematics, or load paths Close collaboration with electrical and controls teams Bias for execution and ownership over documentation and theory

Staff AI Engineer | Sunnyvale, CA | $225K-$300K + Equity We're partnering with a leading company in the software defined vehicle space to hire a Staff AI Engineer. Their technology is already running in more than five million vehicles on the road today and they are now building the next layer of AI that will power future automotive platforms. In this role you will work on advanced language models, retrieval systems and agent style architectures that support real world, safety critical use cases. You will own the full lifecycle of AI systems from early research through to stable, production grade services. What you'll do: Train and fine tune LLMs for reasoning and decision making Build retrieval pipelines and RAG systems for real time semantic search Design and scale ML systems that run in fault tolerant, privacy compliant environments Develop evaluation frameworks to measure reliability, correctness and performance Work closely with engineering and product teams to shape AI solutions that match real world needs What we're looking for: 5+ years of experience as an AI or ML engineer Hands on experience with LLMs, agent frameworks and RAG architectures Strong Python and experience with PyTorch or TensorFlow Background in building and deploying production ML systems Comfort working in a collaborative on site environment three days per week in Sunnyvale If this sounds like something you would like to explore, apply today and we'll be in touch

Do you want to play a defining role in a well backed AI company building the next generation of intelligent agents? Compensation: $220k - $240k Employment Type: Full time Model: Hybrid (days on site, 3 days remote) This company is building AI agents that automate complex, manual workflows across one of the largest and most operationally complex industries in the world. What started with voice, the hardest and highest impact interface, is rapidly expanding into full end-to-end workflow automation across sales, servicing, and claims. The long term vision is to create reasoning agents capable of operating autonomously across entire enterprise systems. With over $70M raised, including a recent large Series B led by top tier venture firms, the company is entering a phase of rapid scale. Engineering is the core of the business, and technical decisions made today will define how intelligent systems operate in real production environments for years to come. The Opportunity: As a Staff Software Engineer, you will be a senior technical leader responsible for shaping foundational systems that power AI-driven products at scale. This role goes far beyond feature delivery. You will own architectural direction, influence platform strategy, and build systems that enable reliable, observable, high-performance AI agents in a regulated, mission-critical environment. You will work with an elite group of engineers, researchers, and product leaders who value strong technical judgment, clear communication, and high ownership. This is a role for someone who thrives in ambiguity, enjoys solving hard infrastructure problems, and wants to see their work have immediate, real world impact. What You Will Do: Define and drive the technical vision for core platforms and domains, including architecture, infrastructure, tooling, and performance Design, build, and operate scalable backend systems that leverage foundational LLMs and asynchronous workflows Lead architectural decisions and trade-offs, balancing speed of iteration with long-term reliability and maintainability Partner closely with product, data science, and infrastructure teams to translate business strategy into durable technical roadmaps Serve as a technical mentor through design reviews, code reviews, and hands-on guidance, raising the bar for engineering excellence Own operational excellence across the stack, including debugging complex issues, participating in on-call, and leading post-mortems Define, measure, and improve reliability metrics such as SLAs, SLOs, and SLIs Identify technical debt and drive initiatives that improve system quality, performance, and developer velocity Introduce new technologies and processes that materially improve how teams build and ship software Represent the engineering organization externally when appropriate through technical talks, open source, or partner engagement What We're Looking For: 8+ years of experience building and operating high-quality production software, with strong depth in Python Demonstrated experience architecting asynchronous, distributed, high-throughput systems in production Strong expertise with Python frameworks such as FastAPI, Django, and asyncio or equivalent Proficiency with Node.js, React, TypeScript, and Express, with sound judgment on when to use each stack Deep knowledge of SQL and experience with distributed messaging and streaming systems such as Kafka, SQS, SNS, or RabbitMQ Solid cloud experience with AWS, GCP, or Azure, including infrastructure as code, CI/CD, and observability Ability to navigate ambiguity, make principled trade-offs, and lead without formal authority Experience working in remote, asynchronous, distributed teams with strong written and verbal communication skills Curiosity and enthusiasm for emerging technologies and their real-world applications Nice to Haves: Hands-on experience working with large language models and techniques to improve reliability, latency, and cost efficiency Experience in regulated or compliance-heavy industries such as insurance, finance, or healthcare Background in high-growth startup environments where systems and teams scaled rapidly Proven track record of mentoring senior and mid-level engineers Public technical contributions through open source, talks, or publications Why This Role: Strong funding, long runway, and clear momentum toward category leadership Ownership over foundational systems that define how autonomous AI agents operate in production High autonomy and trust with direct influence on long-term technical direction A collaborative, high caliber engineering culture that values rigor, learning, and impact The opportunity to help define a new category of applied AI systems used by real customers at scale If you are excited by the chance to shape the core architecture of an AI platform operating in the real world, this role offers both the scope and the ownership to make a lasting impact.

Crossing Hurdles is a global recruitment consultancy partnering with a fast-growing startup (YC W24) which is into orchestrating users' GitHub Action workflows on a fleet of bare-metal gaming CPUs, with build caches co-located next to CI jobs-all enabled by a single line of code. Raised a Series A funding, bringing total capital to $13.5M, and grew ARR from $1M to $3M in just 4 months, continuing to scale rapidly. Role - Product Engineer Location - 5 day/week in NYC/SF Required Tech Stack - React, TypeScript, Golang, Postgres, ClickHouse Compensation - $200k - $300k Benefits - Medical, Vision, and Dental insurance, Unlimited PTO, Quarterly offsite, 12 weeks fully paid parental leave (US) Requirements: 3 - 10 YoE as a great full stack engineer who is 50%-90% frontend leaning but can also work on the backend. Must be product-minded and have worked on customer-facing products Must be proficient in React / TypeScript Why Candidate Should Join: Orchestrates millions of virtual machines each month to run CI jobs efficiently across a proprietary fleet of bare-metal servers. Powers continuous integration for 600+ high-growth startups Founded by elite engineers

A Product Engineer in this role will focus on building and scaling a high-quality AI agent product with strong UX, full‑stack development, and close user collaboration, and should bring 2+ years of startup experience, strong TypeScript skills, and a deep interest in the AI agent space while helping build “high-taste” products for self-learning AI agents and playing a key role in scaling the product to meet growing customer demand while maintaining an exceptional user experience in a rapidly evolving AI agent ecosystem. Responsibilities Collaborate closely with a product designer to ship new features and refine existing user flows based on customer feedback. Engage directly with customers to understand needs, gather feedback, validate ideas, and pitch new features. Develop core product features across the stack (front-end, back-end, and database work) with a focus on quality and reliability. Experiment with new features and technologies, build quick demos for the team, and productionize promising solutions. Contribute to product and design reviews, ensuring the experience is intuitive, polished, and delightful to use. Requirements 2+ years of experience in product, full‑stack, or front‑end engineering at technology startups (Seed to Series E). What we're looking for Strong product sense and attention to user experience; you care about how things feel, not just how they work. High agency and ownership mindset-you proactively find problems, propose solutions, and ship iteratively. Genuine excitement about the AI agent space and improving agent behavior for real users. Comfort working in a fast-moving, experimental environment with tight feedback loops from users and teammates.

🚀 Hiring: Software Engineer / Founding Engineer / Product Engineer 📍 San Francisco (Hybrid / In-Office) 💰 $300,000-500,000 base plus Bonus & Equity We're working with a VC-backed startup building a product at the intersection of engineering, product, and real-world impact. This is a rare opportunity to join early, influence architecture, and help shape what the company becomes. You'll work across front-end, back-end, or full-stack, depending on your strengths and interests. Titles are flexible, as this could be a Founding Engineer, Product Engineer, or Senior Software Engineer role. You'll be trusted to: Build and ship core product features end-to-end Influence technical direction and system design Work closely with founders, product, and design Help define engineering standards as the company scales Tech Stack React + TypeScript (frontend) Python or Node.js (backend) Modern cloud-native tooling What We're Looking For Experience at startup or VC-backed companies (Seed-Series B ideal) Strong fundamentals in React, TypeScript, Python and/or Node Comfort owning problems, not just tickets Product-minded engineers who care about why , not just how Why This Role Early-stage impact: your work directly shapes the product High ownership, high trust environment Strong funding, clear roadmap, ambitious founders Surrounded by sharp, driven people who move fast

Machine Learning Engineer - Applied AI Systems San Francisco, CA - On-site $170k-$250k + equity A venture-backed AI company is expanding its engineering group and looking for a Machine Learning Engineer to help push forward a new generation of decision-support products used in complex, data-heavy environments. The team builds systems that analyse large, unstructured datasets and surface insights that help organisations make high-stakes choices more consistently. You'll join a small group of engineers and researchers working on applied ML problems that combine pattern recognition, anomaly detection, language modelling and real-time data interpretation. This is a hands-on engineering role where you'll prototype, train, evaluate and productionise models that directly shape the product experience. What you'll work on Designing and implementing ML pipelines for processing a wide variety of semi-structured inputs. Training and adapting large language models to handle classification, extraction and reasoning tasks. Developing methods to identify irregularities, inconsistencies and unusual patterns within customer-supplied data. Improving the performance, latency and reliability of deployed models at scale. Collaborating with software engineers to integrate new capabilities into customer-facing features. Exploring new approaches in multimodal modelling, retrieval-augmented generation and adaptive learning systems. Who you might be Someone with professional experience in ML engineering, data science, applied research or similar. Confident programming in Python and fluent with at least one modern deep learning toolkit. Comfortable working with messy, real-world data rather than clean academic datasets. Experience with information extraction, language models, anomaly detection or data quality modelling is valuable. Interested in joining a company where the ML team has genuine influence over product direction. Enjoys experimentation, iteration and solving problems that don't have an obvious starting point. (No strict requirement on years - strength of experience matters more than time served.) Why this is different You'll work on technically challenging problems where accuracy genuinely matters. The company is scaling quickly and investing heavily in expanding its AI group. You'll collaborate closely with product and engineering leadership, not sit in a research silo. The environment is fast-moving, with opportunities to own projects end-to-end. Generous salary, equity and benefits package. Location & Work Style On-site in San Francisco to support a highly collaborative engineering culture. Hybrid flexibility may be available for senior hires already living in the Bay Area.

Mechanical Engineer (Robotics) We are partnering with a robotics company building complex electro-mechanical systems where mechanical design directly determines real-world performance. This role is for someone who doesn't just design parts, but owns motion, reliability, and scale. What You'll Do Own the end-to-end mechanical design of complex electro-mechanical systems with moving parts Design and prototype custom mechanisms and actuators under aggressive timelines Drive concepts from first prototype through high-volume production Personally design parts for volume manufacturing processes, including: Injection molding Die casting Stamping / sheet metal Extrusion Powder metal / MIM Partner closely with contract manufacturers (CMs) to ensure DFM, reliability, and cost targets are met Build systems that are not just elegant but robust, testable, and shippable at scale What We're Looking For Exceptionally strong mechanical intuition, you understand how things move, fail, and improve Proven ability to design and prototype quickly without sacrificing rigor Track record of shipping reliable, hardware products at scale Deep hands-on experience designing custom mechanisms, joints, transmissions, and actuators Experience owning mechanical architecture for complex systems with dynamic loads and tight tolerances Comfortable operating across ambiguity, tight timelines, and high expectations Required Background Currently working at a robotics company (hands-on mechanical role) Background in electro-mechanical systems with real moving parts (not CAD-only work) Experience taking designs from concept → prototype → volume production Ideal Signals Designed robotic arms, legs, mobile platforms, end-effectors, or actuation systems Personally responsible for motor selection, gearing, kinematics, or load paths Close collaboration with electrical and controls teams Bias for execution and ownership over documentation and theory

🚀 Hiring: Software Engineer / Founding Engineer / Product Engineer 📍 San Francisco (Hybrid / In-Office) 💰 $300,000-500,000 base plus Bonus & Equity We're working with a VC-backed startup building a product at the intersection of engineering, product, and real-world impact. This is a rare opportunity to join early, influence architecture, and help shape what the company becomes. You'll work across front-end, back-end, or full-stack, depending on your strengths and interests. Titles are flexible, as this could be a Founding Engineer, Product Engineer, or Senior Software Engineer role. You'll be trusted to: Build and ship core product features end-to-end Influence technical direction and system design Work closely with founders, product, and design Help define engineering standards as the company scales Tech Stack React + TypeScript (frontend) Python or Node.js (backend) Modern cloud-native tooling What We're Looking For Experience at startup or VC-backed companies (Seed-Series B ideal) Strong fundamentals in React, TypeScript, Python and/or Node Comfort owning problems, not just tickets Product-minded engineers who care about why , not just how Why This Role Early-stage impact: your work directly shapes the product High ownership, high trust environment Strong funding, clear roadmap, ambitious founders Surrounded by sharp, driven people who move fast

A Product Engineer in this role will focus on building and scaling a high-quality AI agent product with strong UX, full‑stack development, and close user collaboration, and should bring 2+ years of startup experience, strong TypeScript skills, and a deep interest in the AI agent space while helping build “high-taste” products for self-learning AI agents and playing a key role in scaling the product to meet growing customer demand while maintaining an exceptional user experience in a rapidly evolving AI agent ecosystem. Responsibilities Collaborate closely with a product designer to ship new features and refine existing user flows based on customer feedback. Engage directly with customers to understand needs, gather feedback, validate ideas, and pitch new features. Develop core product features across the stack (front-end, back-end, and database work) with a focus on quality and reliability. Experiment with new features and technologies, build quick demos for the team, and productionize promising solutions. Contribute to product and design reviews, ensuring the experience is intuitive, polished, and delightful to use. Requirements 2+ years of experience in product, full‑stack, or front‑end engineering at technology startups (Seed to Series E). What we're looking for Strong product sense and attention to user experience; you care about how things feel, not just how they work. High agency and ownership mindset-you proactively find problems, propose solutions, and ship iteratively. Genuine excitement about the AI agent space and improving agent behavior for real users. Comfort working in a fast-moving, experimental environment with tight feedback loops from users and teammates.