Mercor is seeking experimental scientists and engineers across inorganic synthesis, characterization, superconductors, and semiconductors (including advanced packaging) to support a frontier AI research lab building models for materials science and the physical sciences. This is hands-on, expert-level work: you'll apply deep, specialized knowledge to generate, structure, and evaluate the scientific data these models learn from — and your input will directly shape how advanced models reason about materials, devices, and processes.
Key Responsibilities:
- Contribute domain expertise across synthesis, characterization, fabrication, and device physics to build high-quality training and evaluation data.
- Review and evaluate AI-generated scientific reasoning, catching errors and improving technical accuracy.
- Design and solve challenging, expert-level problems in your area of specialization.
- Rate and rank model outputs against defined scientific criteria, with clear written reasoning.
- Structure technical knowledge — experimental procedures, characterization results, process data — into well-organized, model-ready data.
- Deliver reliable, high-quality work within defined timelines.
You're a strong fit if you have:
- Hands-on experimental experience in one or more of: inorganic synthesis (solid-state, solution, solvothermal, sol-gel), superconducting materials, or semiconductors and advanced packaging.
- Strong materials or device characterization skills (XRD, SEM, TEM, spectroscopy, electrical/transport measurements).
- Experience with thin-film growth or device fabrication (MBE/epitaxy, MOCVD, CVD, sputtering, IBAD, etch, clean-room microfabrication) — a plus.
- An advanced degree (PhD/MS) or equivalent hands-on experience in materials science, chemistry, physics, or a related engineering field.
- Clear written English and the ability to explain technical reasoning concisely.
Role Details:
- Type: Long-term, ongoing engagement
- Engagement: Up to 40 hours/week (minimum 10)
- Work arrangement: Remote (US-based)