AI Research Engineer for Autonomous Lab Systems

Medra; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Medra is building Physical AI Scientists that operate scientific instruments and analyze results to advance biopharma partnerships. You will join a small, ambitious team shaping the post-training stack and ML direction in a cutting-edge autonomous lab environment.

You will own end-to-end post-training workflows, collaborate with scientists and robotics engineers, and help define the technical strategy for this new ML group.

Qualifications

• Practical experience building AI-driven workflows into the real world.
• Strong problem solving skills for debugging complex systems.
• A clear grasp of probability, statistics, and ML fundamentals.
• Ability to own the post-training stack end-to-end: data pipelines, harnesses, RL environments, and agentic evaluations.
• Proficiency in Python and familiarity with at least one deep learning framework (PyTorch or JAX).
• Experience with LLMs, post-training, reinforcement learning, or agentic systems.

Responsibilities

• Define post-training recipes for our AI models—data collection, experiments, and production integration.
• Build and own post-training data pipelines combining internal and public data.
• Create meaningful evaluations to show models improve protocols and assay development.
• Develop agentic systems with context management and tool calls for insights in lab environments.
• Collaborate with scientists, robotics engineers, and operations to bring reasoning into live loops.
• Shape engineering culture and technical direction of a new ML team.

Skills

Python

Deep Learning

Reinforcement Learning

LLMs

Data Pipelines

Agentic Systems

ML Fundamentals

Tools

PyTorch

JAX

Job description

Medra is building Physical AI Scientists that operate scientific instruments and analyze results to advance biopharma partnerships. You will join a small, ambitious team shaping the post-training stack and ML direction in a cutting-edge autonomous lab environment.

You will own end-to-end post-training workflows, collaborate with scientists and robotics engineers, and help define the technical strategy for this new ML group.