Research and development engineer jobs in San Mateo, CA

Machine Learning Research Engineer - Video Intelligence - Up to $250k A Series A Funded start-up who already have millions in recurring revenue are building next-generation AI infrastructure for video intelligence are looking for an Applied Research Engineer to join their team. What You'll Be Doing Build high-performance video understanding systems and large-scale processing pipelines Tackle ambiguous research problems with creative technical solutions Optimize model performance through clever pre/post-processing, parallelism, and inference optimization Work directly with customers and external teams to deliver end-to-end video intelligence products Collaborate with leading AI video labs on cutting-edge applications What We're Looking For 3+ years experience in computer vision or audio processing Strong Python skills with PyTorch or similar ML frameworks Excellent communication abilities, especially customer-facing Clean, maintainable coding practices Product-minded approach - you want to build complete solutions, not just train models Early startup experience is a plus What's In It For You: Competitive salary up to $250k Small, high-impact team with significant growth trajectory Opportunity to work with top AI video labs and collect world-class datasets Apply now for immediate consideration!

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

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

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.

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.

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

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.

Frontend Engineer Duration: 6+ months (possible extension) Type: W2 Contract (Open to Consider USC, GC, EAD) - No Third Party or C2C Experience: 6+ Years in an Enterprise Environment with BS or MS in Computer Science. Must Have: JavaScript, React.JS, Typescript, NodeJS and REST API Job Summary: Seeking a Frontend Engineer with strong experience in JavaScript, HTML, CSS, and hands-on expertise in React and Node.js. The role involves building scalable, high-quality UI components and collaborating in an Agile development environment. Responsibilities: Develop and maintain frontend modules using JavaScript, HTML, CSS, React, and Node.js. Implement unit testing (JUnit) and ensure code quality. Utilize jQuery and core data structures where applicable. Work closely with cross-functional teams in an Agile/Scrum setup. Participate in solution design, code reviews, and feature development. Required Skills: Bachelor's degree in Computer Science or related field with Strong proficiency in JavaScript, HTML, CSS. Must-have: React.js and Node.js. Experience with unit testing tools (JUnit). Good understanding of data structures and jQuery.

Role: Staff Machine Learning Engineer Duration: Long-term Mode of Interview: Virtual & Final In-person Why this role exists We're building privacy‐preserving LLM capabilities that help hardware design teams reason over Verilog/SystemVerilog and RTL artifacts-code generation, refactoring, lint explanation, constraint translation, and spec‐to‐RTL assistance. We're looking for a Staff‐level engineer to technically lead a small, high‐leverage team that fine‐tunes and productizes LLMs for these workflows in a strict enterprise data‐privacy environment. You don't need to be a Verilog/RTL expert to start; curiosity, drive, and deep LLM craftsmanship matter most. Any HDL/EDA fluency is a strong plus. What you'll do (Responsibilities) • Own the technical roadmap for Verilog/RTL‐focused LLM capabilities-from model selection and adaptation to evaluation, deployment, and continuous improvement. • Lead a hands‐on team of applied scientists/engineers: set direction, unblock technically, review designs/code, and raise the bar on experimentation velocity and reliability. • Fine‐tune and customize models using state‐of‐the‐art techniques (LoRA/QLoRA, PEFT, instruction tuning, preference optimization/RLAIF) with robust HDL‐specific evals: o Compile‐/lint‐/simulate‐based pass rates, pass@k for code generation, constrained decoding to enforce syntax, and "does‐it‐synthesize” checks. • Design privacy‐first ML pipelines on AWS: o Training/customization and hosting using Amazon Bedrock (including Anthropic models) where appropriate; SageMaker (or EKS + KServe/Triton/DJL) for bespoke training needs. o Artifacts in S3 with KMS CMKs; isolated VPC subnets & PrivateLink (including Bedrock VPC endpoints), IAM least‐privilege, CloudTrail auditing, and Secrets Manager for credentials. o Enforce encryption in transit/at rest, data minimization, no public egress for customer/RTL corpora. • Stand up dependable model serving: Bedrock model invocation where it fits, and/or low‐latency self‐hosted inference (vLLM/TensorRT‐LLM), autoscaling, and canary/blue‐green rollouts. • Build an evaluation culture: automatic regression suites that run HDL compilers/simulators, measure behavioral fidelity, and detect hallucinations/constraint violations; model cards and experiment tracking (MLflow/Weights & Biases). • Partner deeply with hardware design, CAD/EDA, Security, and Legal to source/prepare datasets (anonymization, redaction, licensing), define acceptance gates, and meet compliance requirements. • Drive productization: integrate LLMs with internal developer tools (IDEs/plug‐ins, code review bots, CI), retrieval (RAG) over internal HDL repos/specs, and safe tool‐use/function‐calling. • Mentor & uplevel: coach ICs on LLM best practices, reproducible training, critical paper reading, and building secure‐by‐default systems. What you'll bring (Minimum qualifications) • 10+ years total engineering experience with 5+ years in ML/AI or large‐scale distributed systems; 3+ years working directly with transformers/LLMs. • Proven track record shipping LLM‐powered features in production and leading ambiguous, cross‐functional initiatives at Staff level. • Deep hands‐on skill with PyTorch, Hugging Face Transformers/PEFT/TRL, distributed training (DeepSpeed/FSDP), quantization‐aware fine‐tuning (LoRA/QLoRA), and constrained/grammar‐guided decoding. • AWS expertise to design and defend secure enterprise deployments, including: o Amazon Bedrock (model selection, Anthropic model usage, model customization, Guardrails, Knowledge Bases, Bedrock runtime APIs, VPC endpoints) o SageMaker (Training, Inference, Pipelines), S3, EC2/EKS/ECR, VPC/Subnets/Security Groups, IAM, KMS, PrivateLink, CloudWatch/CloudTrail, Step Functions, Batch, Secrets Manager. • Strong software engineering fundamentals: testing, CI/CD, observability, performance tuning; Python a must (bonus for Go/Java/C++). • Demonstrated ability to set technical vision and influence across teams; excellent written and verbal communication for execs and engineers. Nice to have (Preferred qualifications) • Familiarity with Verilog/SystemVerilog/RTL workflows: lint, synthesis, timing closure, simulation, formal, test benches, and EDA tools (Synopsys/Cadence/Mentor). • Experience integrating static analysis/AST‐aware tokenization for code models or grammar‐constrained decoding. • RAG at scale over code/specs (vector stores, chunking strategies), tool‐use/function‐calling for code transformation. • Inference optimization: TensorRT‐LLM, KV‐cache optimization, speculative decoding; throughput/latency trade‐offs at batch and token levels. • Model governance/safety in the enterprise: model cards, red‐teaming, secure eval data handling; exposure to SOC2/ISO 27001/NIST frameworks. • Data anonymization, DLP scanning, and code de‐identification to protect IP. What success looks like 90 days • Baseline an HDL‐aware eval harness that compiles/simulates; establish secure AWS training & serving environments (VPC‐only, KMS‐backed, no public egress). • Ship an initial fine‐tuned/customized model with measurable gains vs. base (e.g., +X% compile‐pass rate, −Y% lint findings per K LOC generated). 180 days • Expand customization/training coverage (Bedrock for managed FMs including Anthropic; SageMaker/EKS for bespoke/open models). • Add constrained decoding + retrieval over internal design specs; productionize inference with SLOs (p95 latency, availability) and audited rollout to pilot hardware teams. 12 months • Demonstrably reduce review/iteration cycles for RTL tasks with clear metrics (defect reduction, time‐to‐lint‐clean, % auto‐fix suggestions accepted), and a stable MLOps path for continuous improvement. How we work (Security & privacy by design) • Customer and internal design data remain within private AWS VPCs; access via IAM roles and audited by CloudTrail; all artifacts encrypted with KMS. • No public internet calls for sensitive workloads; Bedrock access via VPC interface endpoints/PrivateLink with endpoint policies; SageMaker and/or EKS run in private subnets. • Data pipelines enforce minimization, tagging, retention windows, and reproducibility; DLP scanning and redaction are first‐class steps. • We produce model cards, data lineage, and evaluation artifacts for every release. Tech you'll touch • Modeling: PyTorch, HF Transformers/PEFT/TRL, DeepSpeed/FSDP, vLLM, TensorRT‐LLM • AWS & MLOps: Amazon Bedrock (Anthropic and other FMs, Guardrails, Knowledge Bases, Runtime APIs), SageMaker (Training/Inference/Pipelines), MLflow/W&B, ECR, EKS/KServe/Triton, Step Functions • Platform/Security: S3 + KMS, IAM, VPC/PrivateLink (incl. Bedrock), CloudWatch/CloudTrail, Secrets Manager • Tooling (nice to have): HDL toolchains for compile/simulate/lint, vector stores (pgvector/OpenSearch), GitHub/GitLab CI

Analog/Mixed-Signal Verification Engineer San Jose, CA -On-site Full-time/Direct Hire Responsibilities Develop and implement mixed-signal verification and coverage plans for complex IC designs based on design architecture and specifications Design and develop verification testbenches using industry-standard verification languages and methodologies Write and execute test cases to verify mixed-signal circuits for functionality, performance, and reliability Review and analyze verification results, and provide feedback to design teams Collaborate with design and layout teams to identify and resolve design issues Develop new verification methodologies, tools, and techniques, ensuring scalability and portability Sign-off mixed signal designs in preparation for tapeout Write behavioral models from custom analog and mixed-signal circuits in SystemVerilog HDL Collaborate with circuit design teams to understand fine details of custom circuits Collaborate with Design Verification team to craft hooks into the behavioral models for effective verification Run various simulations and equivalence checks to ensure that the model matches closely with the custom circuits Write scripts and simple tools for automating repetitive tasks Optimize and refine models to ensure accuracy while maintaining efficient simulation performance Review and analyze verification results, and provide feedback to design team Document modeling techniques and results for internal and external dissemination Keep updated with industry trends in modeling techniques Requirements Bachelor's degree in Electrical Engineering and 5+ years of relevant industry experience or equivalent Strong understanding of analog and mixed-signal circuit design and verification principles Ability to write test plans, present results, and communicate clearly with multi-functional teams Have a familiarity with verification methodologies and tools: simulators, waveform viewers, execution automation, simulation time optimization, and coverage collection Familiarity with analog behavioral models is a plus Deep knowledge of Verilog/SystemVerilog with ability to write synthesize-able and behavioral code Deep knowledge of digital logic gates, clocking and state elements Deep knowledge of SPICE simulation, HDL simulation and logic equivalence tools Working understanding of analog circuit architecture such as ADC, DAC, LDO, Charge pump, etc. Have good programming skills and can write efficient programs or scripts in Perl, Python, and/or C Excellent debugging, problem-solving and analytical skills Strong communication and teamwork skills -- Vilayath Khan ************************** Manager-TA

Role: Senior Digital Twin ML Engineer Salary: upto $250,000 Work on advanced AI-driven physical systems with broad manipulation and experimental capability. I'm seeking a Senior Digital Twin ML Engineer to build high-fidelity digital twins of robotic, electromechanical, and experimental platforms. You will design model-identification pipelines, calibration routines, dynamic-model learning systems, and multi-scale physics representations that support accurate predictive simulation and closed-loop interaction with RL, planning, and control stacks. This role blends physics intuition, ML modeling, and hands-on experimentation to ensure digital twins remain stable, accurate, and continuously updated as real systems evolve. Responsibilities: Build model-identification and parameter-estimation pipelines with adaptive calibration. Develop ML-based dynamic models, multi-scale physics approximators, and hybrid simulation frameworks. Maintain twin fidelity, stability, and version consistency as data and hardware change. Work closely with simulation, RL, controls, and agent teams to integrate twins into decision-making and learning workflows. Qualifications: Strong experience creating or calibrating digital twins or dynamic, data-driven physics models. Knowledge of system identification, time-series modeling, and physical parameter estimation. Ability to combine physics, ML, and experimental data into robust predictive models. Comfort operating across ML, simulation tooling, and physical hardware interfaces in a fast-paced environment.

We're a fast-moving Series A startup on a mission and we're looking for a Compiler Engineer who can turn cutting-edge ideas into blazing-fast reality. If you live and breathe compilers, know your way around low-level codegen, and love squeezing every last drop of performance from hardware, this is your moment. What You'll Bring 4+ years crafting compilers, with deep mastery of algorithms and data structures Hands-on expertise in low-level code generation, object file manipulation, and target-specific optimizations Serious C/C++ chops Clear communicator, strong doc writer, detail-driven, and always team-first Bonus Points MS/PhD in CS/CE/EE Familiarity with instruction selection, register allocation, dominance, def-use, calling conventions, linking & relocations LLVM experience Loop optimization wizardry (vectorization, unrolling, fusion, parallelization) Why Us? You won't be a cog. You'll be a cornerstone. Own major pieces of the toolchain, shape architecture decisions, and ship tech that pushes the boundaries of what's possible. If you want to build boldly, optimize ruthlessly, and leave your fingerprints on the future, we want to meet you.

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.

We are seeking an AI Scientist /Engineer to join our team in developing and supporting materials discovery and design. The ideal candidate will have strong experience building AI-based solutions for building neural network architecture, attention mechanisms, multi-modal learning, aggregating and structuring training data, statistical theory, and cloud-based compute for parallelized, scalable, and automated workflows. Key Responsibilities: Design, develop and deploy multi-modal AI, ML, and hybrid physical-based models to solve ground-breaking material physics and design problems. Aggregate, process, transform and quality-control experimental and simulation data for modeling and analysis. Design, develop, and maintain data workflows to support materials informatics initiatives. Optimize data pipelines and model execution on parallel cloud systems (e.g., Azure, GCP, AWS). Collaborate with materials scientists, chemists, and software engineers to integrate analytics and predictive modeling into core R&D workflows. Document code, workflows, and best practices to support reproducible research. Apply AI and data analytics to optimize material synthesis and processing parameters in real-time, minimizing defects, improving consistency. Build materials-informatics pipelines combining DFT/MD simulations, high-throughput experiments, and fab/metrology data to learn process-structure-property relationships for materials used in CVD/ALD/etch equipment. Develop deep learning models for forecasting thermal, mechanical, chemical, and plasma-compatibility behavior of candidate materials. Technical Skills: Strong proficiency in programming languages like Python and C++. Experience with machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow). Knowledge of generative modeling techniques and architectures (e.g., GANs, VAEs, transformers). Knowledge of MLOps, model deployment pipelines, and CI/CD. Experience with data cleansing, preprocessing, and feature engineering Qualifications: Graduate or undergraduate degree in Computer Science, Engineering, Applied Mathematics, or a related technical field. 2-4 years of work experience (depending on educational degree) in data science, AI, machine learning, or data engineering roles. A strong foundation in the principles of materials science is essential to understand the underlying science and set up meaningful problems for AI. Expert in Python and data science libraries (e.g., pandas, NumPy, scikit-learn, TensorFlow or PyTorch). Expertise in use of cloud-based compute environments and tools for parallel or distributed computing. Strong problem-solving and communication skills. Best Regards, Bismillah Arzoo (AB)

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.

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.

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

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!