We're an AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and beyond. Backed by world-class investors and growing rapidly, we operate at the pace the frontier requires. Our team brings deep expertise, genuine ownership, and an insatiable drive to push the boundaries of what's scientifically possible.
About the Role
Join our team of scientists and engineers building a lab where AI and automation speed up materials discovery.
We're building an autonomous lab to speed up materials discovery, and we need someone who understands materials R&D from the inside — someone who's run the experiments, fought with the instruments, and knows what "the workflow" actually means at the bench. As our Research Engineer, you'll work directly with scientists to understand what they're trying to learn, then translate that into the hardware setups, instrument sequences, and engineering requirements that make it possible to automate.
What You'll Do
Work closely with bench scientists to understand experimental goals and turn them into concrete hardware and workflow requirements.
Evaluate, select, and configure lab instrumentation and hardware to support new and existing materials R&D workflows.
Design experimental and automation workflows that hold up to the realities of materials synthesis and characterization.
Serve as the technical bridge between scientists and the automation/software engineering team, making sure integration specs reflect how the science actually works.
Troubleshoot instrument and workflow issues that require materials domain knowledge to diagnose.
Collaborate with AI and data scientists to help shape how experimental data is structured and used for analysis and planning.
You Will Thrive in This Role If You Have
PhD in Materials Science, Chemistry, Chemical Engineering, or a related field (or equivalent research experience).
Strong working knowledge of common materials lab hardware (e.g. furnaces, fluid/gas handling manifolds, characterization tools, synthesis equipment) and the workflows built around them.
Ability to communicate fluently with both scientists and engineers, and to translate scientific intent into clear technical requirements.
Comfort writing Python to interact with instruments, manipulate experimental data, and prototype automation workflows
Especially Strong Candidates May Also Have
Prior experience working alongside automation or software engineers.
Experience with electronic lab notebooks, LIMS, or other lab data systems.
A track record of designing or adapting experimental protocols for higher-throughput or automated execution.
Mechanics
Minimum education: PhD or equivalent combination of education and hands-on research experience
Location: Menlo Park, CA (Soon: San Francisco, too)
Compensation: $200,000-$250,000 + equity
Visa sponsorship: Yes, we sponsor visas.