ALD experts develop and troubleshoot deposition processes, then rate and rank AI reasoning about recipes, precursors and film characterization. It suits US-based chemists, physicists or process engineers with hands-on ALD experience and an advanced degree or equivalent practice.
Sobre la vacante
Mercor is seeking experts in Atomic Layer Deposition (ALD) and thin-film processes to support a frontier AI research lab building models for semiconductors 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 deposition, materials, and semiconductor processes.
Key Responsibilities:
- Contribute domain expertise across ALD process development, precursor chemistry, and thin-film characterization 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 ALD and semiconductor processing.
- Rate and rank model outputs against defined scientific criteria, with clear written reasoning.
- Structure technical knowledge — process parameters, recipes, characterization results — into well-organized, model-ready data.
- Deliver reliable, high-quality work within defined timelines.
You're a strong fit if you have:
- Hands-on experience developing, optimizing, or troubleshooting ALD processes.
- Deep knowledge of thin-film deposition for semiconductor or advanced-packaging applications.
- A strong grasp of precursor chemistry and surface reaction mechanisms.
- Experience with materials characterization (XRD, SEM, TEM, XPS, ellipsometry, etc.).
- An advanced degree (PhD/MS) or equivalent hands-on experience in materials science, chemistry, chemical engineering, or physics.
- Clear written English and the ability to explain technical reasoning precisely.
Role Details:
- Type: Long-term, ongoing engagement
- Engagement: Up to 40 hours/week (minimum 10)
- Work arrangement: Remote (US-based)
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