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Research Engineer - Autonomous Materials Discovery Lab

felicis • United State
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AI Summary

Build and operate an autonomous lab to accelerate materials discovery by translating scientific goals into hardware and automation workflows. Design experimental protocols and serve as technical bridge between bench scientists and automation teams. Requires PhD-level materials science expertise with hands-on lab instrumentation experience.

Key Highlights
PhD in Materials Science, Chemistry, Chemical Engineering or equivalent research experience required
Design and implement hardware setups and automation workflows for materials R&D
Bridge between bench scientists and automation/software engineering teams
Key Responsibilities
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
Technical Skills Required
Materials lab instrumentation Python programming Experimental workflow design
Benefits & Perks
Compensation: $200,000-$250,000 + equity
Visa sponsorship available
Nice to Have
Prior experience working alongside automation or software engineers
Experience with electronic lab notebooks, LIMS, or other lab data systems
Track record of designing or adapting experimental protocols for higher-throughput or automated execution

Job Description


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 and will do everything we can to assist in this process.

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