Research and development engineer jobs in Santa Rosa, CA

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

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

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

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). Proficiency in TypeScript, with experience either across the stack or in front‑end‑leaning roles. Experience at a high‑taste product company or at an AI/agent‑native startup. Undergraduate degree in Computer Science, Engineering, or a related field. 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.

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.

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.

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

You'll work closely with our product, engineering, and security teams to build scalable decentralized systems that push the boundaries of what's possible on-chain. Key Responsibilities: Design, write, test, and deploy smart contracts on Ethereum or other EVM-compatible blockchains. Collaborate with frontend and backend developers to integrate smart contracts into decentralized applications (dApps). Conduct peer reviews, optimize gas efficiency, and maintain best practices for security. Develop automated testing frameworks to ensure contract reliability. Stay up to date with emerging blockchain protocols, development tools, and security standards. Participate in smart contract audits and coordinate fixes for any identified vulnerabilities. Contribute to technical documentation for contracts and protocols. Requirements: Proven experience developing and deploying smart contracts in Solidity (or Rust, for non-EVM chains). Strong understanding of blockchain fundamentals, consensus mechanisms, and token standards (ERC-20, ERC-721, ERC-1155). Experience with smart contract development tools such as Hardhat, Foundry, Truffle, or Remix. Familiarity with Ethereum and Layer 2 scaling solutions (e.g., Arbitrum, Optimism, Polygon). Understanding of web3 libraries (ethers.js, web3.js) and dApp integrations.

About Us Mintegral is a leading programmatic and interactive mobile advertising platform, starting from the APAC region and radiating out globally. Powered by advanced AI technology, we provide global advertisers and developers with innovative, comprehensive experiences. With our efficient mobile marketing and monetization solutions, we help our clients exceed their marketing goals. As a self-developed programmatic platform, since Launched in 2015, Mintegral has quickly grown to become one of the largest mobile advertising platform in Asia. We offer a full stack of programmatic products and services including our Self-service Platform, DSP, SSP, Ad Exchange and DMP. We have also created the Mindworks Creative Studio, which offers publishers and brands cutting-edge creative solutions, from traditional creative right through to the latest interactive ad formats. For more information, please visit our website: ***************************** About the Role We are looking for a highly motivated Machine Learning Engineer to help advance the intelligence of our advertising platform. You will work across the full lifecycle of ML development-from framing ambiguous problems to deploying large-scale production models that directly impact advertiser ROI and user experience. Responsibilities Own the end-to-end algorithm development lifecycle, including problem formulation, solution design, experimental validation, and online deployment. Leverage data analysis and algorithmic innovation to optimize model inference performance, enhance monitoring systems, and continuously improve both monetization efficiency and user experience within the advertising platform. Identify potential issues and optimization opportunities across the ad delivery system. Actively participate in technical discussions, stay proactive in learning, and apply new technologies to solve real-world problems. Track cutting-edge research in machine learning and incorporate advanced techniques into practical adtech applications. Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, AI, Mathematics, Physics, or a closely related technical field; strong academic background preferred. Excellent problem-solving skills, with the ability to abstract complex problems, build models, and analyze large datasets. Strong engineering fundamentals and production-quality coding skills (Python, C++, or related languages). Self-driven, resilient, and able to navigate challenging problems with a proactive mindset. Hands-on experience with optimizing ad systems end-to-end, and understanding system behavior through data loops and feedback cycles. Practical experience with feature engineering, model architecture design, and sample distribution analysis; background in generative recommendation or LLM-based approaches is a plus. Experience in RTB and ads strategies, such as cold-start optimization, budget pacing, calibration, or bidding strategies, is strongly preferred.

Previous Pharmaceutical/Biotech experience is mandatory for this role. MMR Consulting is an engineering and consulting firm specializing in the pharmaceutical and biotechnology industries. Its services include Engineering, Project Management, and other Consulting services. MMR Consulting has offices in Canada, USA, and Australia. This is an outstanding opportunity to join our growing team, where the successful candidate will work with a group of engineers and specialists involved in project management, commissioning and qualification, of equipment, systems and facilities. The work will require working out of the client's facilities in San Francisco Bay Area, California. This role is for Bioprocess Sr. C&Q Engineer role to work on the commissioning, qualification, startup of upstream and downstream bioprocess systems/equipment in the biopharmaceutical industry, as well as process equipment in pharma/biotech industries. The ideal candidate should possess leadership skills to lead/mentor intermediate/junior engineers. Responsibilities Provide technical guidance into the commissioning, qualification and start-up of various equipment and facilities used in life science manufacturing, such as bioreactors, tanks, CIP, Buffers, Media, Chrom, TFF, washers & autoclaves, etc. Lead the development of key qualification deliverables during the project lifecycle to ensure project is well defined, and the action plan to test the system is applicable and relevant. Lead qualification processes throughout the project lifecycle such as VPP, Risk Assessments, RTM, DQ, FAT, SAT, IQ, OQ and PQ as appropriate to ensure timely completion and to ensure all quality and engineering specifications are met. Prepare protocols, execute protocols, summarize data, resolve deviations, prepare final reports. Experience with C&Q of process equipment, utilities, facilities is an asset. Thermal Validation experience is an asset. Coordinate meetings with cross-functional departments, to drive project progress, facilitate decisions, provide updates. Engage other departments, as required, for design reviews and decisions. Travel may be occasionally required for meetings with clients, equipment fabrication vendors or Factory Acceptance Testing (FATs). Work may require occasional support over shutdowns or extended hours, specifically during installation and commissioning / validation phases. Client-management (maintain key Client relationships in support of business development and pursuit of new work), project scheduling/budgeting, coordination of client and MMR resources for effective project delivery, supporting business development (providing technical support to the sales as required for proposals/opportunities), presenting at industry conferences/publishing papers etc. Visit construction and installation sites following all site safety requirements. Other duties as assigned by client, and/or MMR, based on workload and project requirements. Qualifications 8-12+ years for years of experience in commissioning, qualification or validation of various systems within the pharmaceutical/biotech industry. Excellent written and spoken English is required including the preparation of technical documents in English Knowledge of requirements for a cGMP operations, including SOPs, Change Controls, Validation. Experience with developing and executing validation projects. Risk-Based Commissioning & Qualification approaches, such as ASTM E-2500 or ISPE ICQ, is considered an asset, but not required. Experience with commissioning and qualification of biotech process equipment (upstream or downstream or both), such as some, but not all, of the following: fermentation, bioreactors, downstream purification processes (chromatography, TFF, UF) is required Experience with commissioning & qualification of process control systems (i.e. PCS, SCADA, Historians) and building automation systems (i.e. Siemens Insight / Desigo, JCI Metasys) are considered an asset, but not required. Experience with Qualification or Validation of clean utilities, ISO clean rooms, and Thermal Validation is considered an asset. Experience with preparation and execution of URS's, DQ's, RTMs, Risk Assessments, CPPs, VPPs, FATs, SATs, IOQs, NCRs, Final Reports. Ability to lift 50 lbs. Engineering or Science degree, preferably in Mechanical, Electrical, Chemical, Biochemical, Electromechanical or a related discipline. Ability to handle multiple projects and work in a fast-paced environment. Strong multi-tasking skills Salary range: 100,000$ -145,000$ based on experience. Equal Employment Opportunity and Reasonable Accommodations MMR Consulting is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Our hiring decisions are based on merit, qualifications, and business needs. We are committed to working with and providing reasonable accommodations to individuals with disabilities globally. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application or interview process, please let us know the nature of your request.

At Mercor, we're building the talent engine that helps leading labs and research orgs move AI forward. Our latest initiative focuses on benchmarking and improving model performance and training speed across real ML workloads. If you're an early-career Machine Learning Engineer or an ML PhD who cares about innovation and impact, we'd love to meet you. ## What to Expect As a Machine Learning Engineer, you'll tackle diverse problems that explore ML from unconventional angles. This is a remote, asynchronous, part-time role designed for people who thrive on clear structure and measurable outcomes. - **Schedule:** Remote and asynchronous-set your own hours - **Commitment:** ~20 hours/week - **Duration:** Through December 22nd, with potential extension into 2026 ## What You'll Do - Draft detailed natural-language plans and code implementations for machine learning tasks - Convert novel machine learning problems into agent-executable tasks for reinforcement learning environments - Identify failure modes and apply golden patches to LLM-generated trajectories for machine learning tasks ## What You'll Bring - **Experience:** 0-2 years as a Machine Learning Engineer or a PhD in Computer Science (Machine Learning coursework required) - **Required Skills:** Python, ML libraries (XGBoost, Tensorflow, scikit-learn, etc.), data prep, model training, etc. - **Bonus:** Contributor to ML benchmarks - **Location:** MUST be based in the United States ## Compensation & Terms - **Rate:** $80-$120/hr, depending on region and experience - **Payments:** Weekly via Stripe Connect - **Engagement:** Independent contractor ## How to Apply 1. Submit your resume 2. Complete the System Design Session (< 30 minutes) 3. Fill out the Machine Learning Engineer Screen (research organizations. Our investors include **Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey**. Thousands of professionals across law, creative fields, engineering, and research use Mercor to work on frontier projects shaping the next era of AI.

Role : Senior Cloud Engineer (AWS) Duration: Long Term Contract Job Description: Cloud Engineer Core Competencies: Core AWS Cloud Engineer with experience in DevOps skills, Agile skills, ability to operate platforms at scale, has done automation, with a focus on maturing the cloud platform. AWS IAM identity-based and resource based policies AWS Networking (route tables, transit gateways, security group rules, VPC, subnets, R53 etc.) AWS CloudWatch and CloudTrail x troubleshooting issues AWS glue AWS Redshift RDS MSSQL Splunk Experience with CI/CD pipelines for infrastructure deployments. Experience with Harness would be a plus, but experience with other CI/CD tools (ArgoCD, CircleCI, Git Hub Actions, Jenkins, etc.) is acceptable. Terraform Experience with Centralized secrets store (AWS Secrets Manager). Git management best practices EKS and k8s cluster management SSO via Okta and role-based access control Experience with Agile project management (scrum and kanban) concepts: sprints, sprint planning, backlog grooming, story points, ticket life-cycle and management.

Job Description: Cloud Engineer Core Competencies: Core AWS Cloud Engineer with experience in DevOps skills, Agile skills, ability to operate platforms at scale, has done automation, with a focus on maturing the cloud platform. AWS IAM identity-based and resource based policies AWS Networking (route tables, transit gateways, security group rules, VPC, subnets, R53 etc.) AWS CloudWatch and CloudTrail x troubleshooting issues AWS glue AWS Redshift RDS MSSQL Splunk Experience with CI/CD pipelines for infrastructure deployments. Experience with Harness would be a plus, but experience with other CI/CD tools (ArgoCD, CircleCI, Git Hub Actions, Jenkins, etc.) is acceptable. Terraform Experience with Centralized secrets store (AWS Secrets Manager). Git management best practices EKS and k8s cluster management SSO via Okta and role-based access control Experience with Agile project management (scrum and kanban) concepts: sprints, sprint planning, backlog grooming, story points, ticket life-cycle and management.

Velocity Tech has partnered with an exciting tech start-up that is looking for multiple Backend Developers to join their team. This role will be on-site in San Francisco. They are currently seed-funded with a runway of 2+ years but looking to raise their series A next year. What You'll Do Develop high-quality data pipelines pulling events, conversion values, and LTV signals from Snowflake, Databricks, and Redshift. Scrape and process unstructured data from social platforms and ad libraries, using LLMs to turn it into structured inputs. Own the logging and observation framework that captures every system and market state change. What You Bring 4+ years of backend engineering experience (Python). Strong systems thinking and focus on data accuracy. Comfort working across SQL, NoSQL, streaming, and queueing systems. High ownership mindset and willingness to dive deep into data issues. Nice to Have Experience with real-time or low-latency systems. Background in complex scraping or working without strong APIs. Familiarity with distributed, event-driven architectures (Kafka, RabbitMQ). Experience with large-scale ETL using Airflow, dbt, or Spark.

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

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). Proficiency in TypeScript, with experience either across the stack or in front‑end‑leaning roles. Experience at a high‑taste product company or at an AI/agent‑native startup. Undergraduate degree in Computer Science, Engineering, or a related field. 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.

Senior ML Infra Engineer - San Francisco or Redwood City, CA A company who are building AI systems with general physical ability are looking for a Senior ML Infra Engineer to join their team to build and maintain infrastructure for training, RL workflows, data pipelines, and model deployment. What Will I Be Doing: Build and maintain scalable infrastructure for distributed model training, fine-tuning, RLHF/DPO workflows, and large-scale experiments. Develop data pipelines, dataset versioning systems, and experiment tracking tools to ensure reproducibility and traceability. Operate containerized training and inference environments, CI/CD pipelines for models, and automated evaluation workflows. Collaborate with LLM researchers, RL scientists, data engineers, and systems teams to support rapid experimentation and reliable model deployment. Who We're Looking For: Deep experience in ML infrastructure, distributed training, experiment management, or production ML systems. Familiarity with containerization, orchestration, model runners, dataset governance, and evaluation pipelines. Proven ability to design robust training and deployment workflows that support high-throughput experimentation. Comfortable working across ML, infrastructure, data, and engineering teams in a fast-paced, high-precision environment. What's In It For Me: Salary of $200k-$300k dependent on experience plus equity Ownership of critical ML infrastructure powering real-world AI experimentation Work at the forefront of AI, robotics, and scientific discovery Apply now for immediate consideration!

A frontier AI company is building systems that can act in the physical world, experimenting, engineering, and executing multi-step processes with real-world constraints. Backed by major research funding and operating at the edge of physical-AI innovation, they're creating capabilities that don't exist anywhere else. Join to work from first principles, own high-impact systems end-to-end, and help define how agentic AI will operate complex workflows in the real world. Why This Role Matters Build agent systems that plan, execute, and recover across intricate engineering workflows Shape foundational behaviour patterns for next-gen LLM tool-use Join early enough to influence architecture, culture, and performance standards Work on problems that sit far beyond typical “LLM app” engineering What You'll Do Develop planners, state machines, and tool-calling flows using frameworks like LangGraph Create schemas, action definitions, and cross-tool interfaces for reliable, traceable execution Build error-handling, timeouts, retries, rollbacks, and replay mechanisms Partner with ML, infra, and systems teams to integrate agents into real engineering toolchains What You Bring Strong experience with agent systems, structured tool calling, or orchestration frameworks Deep intuition for schemas, deterministic execution, and multi-step workflow design Ability to model failure modes, edge cases, and safe interactions in complex systems Comfort working across AI, systems engineering, and specialised domain tools in a high-precision environment