--- title: 'Full Stack Software Engineer at Medra' canonical: 'https://feeny.ai/job/full-stack-software-engineer-medra-san-francisco-bvht2fk1neme' type: 'job' last_seen: '2026-09-08' --- # Full Stack Software Engineer at Medra - **Company:** Medra - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-05-13 - **Last confirmed live:** 2026-09-08 - **Apply:** https://jobs.ashbyhq.com/medraai/4b14a964-094b-4bb8-9e92-d0ae183b8e1b ## Job description ## WHAT WE'RE BUILDING: If you want to shape the future of science, come build with us. Medra is building Physical AI Scientists: robotic systems that work hand-in-hand with leading biopharma partners to enable scientific breakthroughs faster than ever before. 🤖 Physical AI that can operate scientific instruments with human-level dexterity. 🧪 Scientific AI that can analyze results, reason about next steps, and close the loop autonomously. We shipped our first production system over a year ago, recently raised a $52M Series A, and are opening one of the largest autonomous labs in the US. We're a small, ambitious team and you'd be joining early. ## THE TEAM: - We’re a team of passionate, mission-driven engineers from companies like Tesla, Amazon, SpaceX, and Neuralink. We’re collaborative and love moving fast, both with our product and on team trips skiing or go-karting! - As a team, we love nerding out about engineering and robotics — plus other topics like race cars or cooking. We like learning new things and then sharing our new knowledge with each other. - Our team is opinionated and straightforward. We don’t mind intense discussions about design tradeoffs. If we have arguments or miscommunication, we resolve conflicts quickly and empathetically. ## IN THIS ROLE, YOU WILL: - Build and own the tools our customers use to design, monitor, and analyze autonomous experiments - Develop internal systems that help our team deploy, operate, and debug a growing fleet of robots in real lab environments - Work across the full stack, from React frontends to Node and Python services to AWS infrastructure, shipping features end-to-end - Collaborate directly with scientists, operations, and robotics engineers to understand their workflows and build software that makes their work easier and faster - Shape the engineering culture and technical direction of a product that's redefining how life science R&D gets done Let's talk if you have: - 3+ years of full-stack engineering experience at product-driven companies - Practical experience building AI-driven workflows into products - Strong proficiency in Python and TypeScript, with experience building production React applications - Comfort working across the stack: frontend UI, backend services, cloud infrastructure (AWS) - A track record of shipping end-to-end. You've taken features from idea to production, not just written code to spec - A bias toward action and ownership. You thrive when things are loosely defined and move fast - Genuine curiosity about what you're building and who you're building it for ## About Medra ## Company Overview - **One-liner**: Building autonomous Physical AI for the lab to accelerate scientific discovery by executing and optimizing experiments in a closed loop. - **Entity Type**: Private (Series A) - **Headquarters**: San Francisco, California, United States (340 Pine Street, Suite 100) - **Founded**: 2021 (some sources cite 2022 – conflicting reports) - **Founders**: Michelle Lee (CEO) ## Core Business - **Primary industries**: Life sciences automation, laboratory robotics, AI-driven experimental design - **Target customers**: B2B – biopharma companies, academic research labs, government agencies (e.g., DARPA) - **Mission / purpose**: Unlock breakthroughs at scale by tightly integrating AI scientific reasoning with physical experimentation. ## Products & Services - **Physical AI Lab (Medra Lab 001 – ML001)**: A fully autonomous robotic workcell that executes wet-lab protocols (e.g., CRISPR, cell culture, NGS) using computer vision and robotic manipulation. Instrument-agnostic and modular. - **AI Experimentalist**: The scientific reasoning layer that translates natural-language research goals into executable experiment plans, coordinates multi-step protocols, analyzes results, and refines methods in a closed loop. - **Platform Type**: Physical AI + Scientific AI as a service (on-site deployment or remote operation via ML001). ## Market Standing - **Valuation / Market Cap**: Not publicly disclosed - **Key Metric**: Total funding of $63M (Series A of $52M closed December 2025, preceded by $11M pre-seed in October 2025 and a non-equity assistance from PharmStars in 2023) - **Notable Investors / Partners**: Human Capital (lead), Lux Capital, Menlo Ventures, Catalio Capital, Neo, 776 (Seven Seven Six), Fusion Fund, Nat Friedman & Daniel Gross - **Growth Signals**: - Headcount grew 100% YoY (31 employees as of mid-2026) - Launched ML001 in San Francisco (April 2026) — largest autonomous lab in the U.S. - Announced DARPA collaboration (June 2026) to advance natural-language-to-executable-experiment capabilities - 8 open positions across biology, engineering, design, and operations ## Competitive Advantages - **Closed-loop integration**: Combines physical execution with AI-driven experimental design and learning – not just robotic task automation. - **Instrument-agnostic & modular**: Works with both manual and automated lab instruments, allowing easy swapping of modules and protocols. - **Natural-language programming**: Scientists can edit protocols in plain English (written or voice). - **Scalable data generation**: Logs every action, video, and metadata per sample for traceability and model training. ## Strategic Focus - Expand partnerships with biopharma, academia, and government (DARPA is a key early customer). - Advance the AI Experimentalist layer to enable full autonomous hypothesis generation and validation. - Scale deployments of Physical AI Labs on-site and remotely through ML001. ## Why Work Here - **Culture**: Described as “intense curiosity and rigorous debate” with clear, direct communication and quick resolution of conflicts through mutual respect. - **Team**: Community of diverse thinkers, “not just a company but a movement to transform biotechnology.” - **Work policy**: Likely on-site at the San Francisco lab given the nature of physical robotics; no explicit remote/hybrid policy mentioned. - **Perks & highlights**: Opportunity to work on cutting-edge AI + robotics with a high-impact mission; funded by top-tier VCs; strong engineering culture (43% technical staff, many from Neuralink, Applied Intuition, Amazon, Carnegie Mellon). ## Sources 1. [medra.ai](https://www.medra.ai/) 2. [medra.ai/careers](https://www.medra.ai/careers) 3. [linkedin.com/company/medra-ai](https://www.linkedin.com/company/medra-ai) 4. [cbinsights.com/company/medra](https://www.cbinsights.com/company/medra) 5. [medra.ai/darpa-collaboration](https://www.medra.ai/darpa-collaboration) 6. 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