Remote ALD Process Expert for AI‑Driven Semiconductors

Mercor; New York (NY); Remote; USD 120,000 - 180,000; Full time

Job summary

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.

Qualifications

• Hands-on ALD process development, optimization, or troubleshooting.
• Deep knowledge of thin-film deposition for semiconductor/advanced‑packaging.
• Strong understanding of precursor chemistry and surface reactions.
• Experience with materials characterization techniques (XRD, SEM, TEM, XPS, ellipsometry).

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.

Skills

ALD processes

Thin-film deposition

Precursor chemistry

Materials characterization

Clear written English

Education

PhD or MS in materials science/chemistry/chemical engineering/physics

Job description

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.