Forward Deployed Robotics Engineer

Medra•San Francisco, CA

12d•$130,000 - $210,000•Onsite

About The Position

Medra is building a Physical AI Scientist platform that enables AI to operate scientific instruments with human-level dexterity and analyze results, reason about next steps, and autonomously close the loop. The Forward Deployed Robotics Engineer will own end-to-end delivery of high-impact customer projects, define roadmaps for customers’ scientific challenges, and translate scientific workflows into technical requirements. The role supports system architecture and develops interfaces between robots, instruments, and software. The engineer will design, build, test, integrate, and debug scientific workflows using the platform, combining existing capabilities with production software and instrument integrations. The work spans simulation and physical robots, customer-site bring-up, integration testing, water runs, and scientific validation. The engineer will diagnose issues across software, instruments, robotics, and customer infrastructure; extend deployed systems for new instruments, consumables, and workflows; and bring deployment learnings back into the platform through reusable integrations, tests, diagnostics, and tooling. The role requires communicating technical decisions, limitations, and risks clearly to customers and teammates. This is a 100% in-person position at Medra’s San Francisco office, with approximately 30% travel to customer sites for hands-on deployment and support. Relocation benefits are offered for applicants who need to relocate.

Requirements

Strong software engineering fundamentals and experience shipping production code.
Demonstrated systems thinking, including designing, implementing, testing, or debugging interfaces in a production system.
Experience delivering technical solutions with customers or users, from an ambiguous problem to a working solution in use.
Enjoy working directly with users, making technical decisions, and being accountable for results.
Ability to learn unfamiliar technologies quickly and make sound decisions with incomplete information.
Clear written and verbal communication, including the ability to explain technical tradeoffs and surface problems early.
Interest in developing depth in robotics, automation, and physical AI, with willingness to work directly with physical systems.
Ability to work in person at the San Francisco office and travel to customer sites approximately 30% of the time.

Nice To Haves

Experience shipping a product that combines software and hardware.
Forward deployed engineering experience or another engineering role with direct responsibility for customer implementations.
Production code experience in Python, C++, or Rust.
Experience designing APIs, distributed systems, or software that coordinates external services and equipment.
Experience designing integration tests, reliability tests, observability, or deployment tooling.
Experience with robotics, laboratory automation, or biology.

Responsibilities

Own end-to-end delivery of high-impact customer projects and define roadmaps addressing customers’ critical scientific challenges.
Translate scientific workflows into technical requirements, support system architecture from conception through delivery, and develop interfaces between robots, instruments, and software.
Design, build, and test scientific workflows on the Physical AI Scientist platform, combining existing capabilities with production software and instrument integrations.
Make implementation tradeoffs with robotics and software engineers, determining when to reuse existing capabilities and when new engineering is needed.
Integrate, test, and debug software solutions in simulation and on physical robots.
Work with forward deployed scientists on integration testing, water runs, customer-site bring-up, and scientific validation, resolving engineering blockers.
Diagnose failures across software, instrument behavior, robotics, and customer infrastructure, working with specialist engineers to resolve them.
Extend deployed systems to support new instruments, consumables, and workflows, and roll out releases with appropriate verification and clear operating guidance.
Generalize integrations and share reusable tests, diagnostics, and tooling with other deployment teams.
Explain technical decisions, limitations, and risks clearly to customers and teammates.
Travel to customer sites approximately 30% of the time for hands-on deployment and support.