Atomic Layer Deposition (ALD) Experts

HumanitApp; Northern (KY); Hybrid; USD 98,000 - 134,000; 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 that shapes how models reason about deposition and materials.

You will contribute domain expertise, review AI-generated reasoning, and design solutions to optimize data and model performance in remote, US-based engagement.

Qualifications

• 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.

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 expertise

Thin-film deposition

Precursor chemistry

Materials characterization

Technical writing

Education

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

Tools

XRD

SEM

TEM

XPS

Ellipsometry

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.

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)

AI evaluation Physics Research

Who this role may fit

This opportunity may suit professionals with relevant experience in AI evaluation, Physics, Research. Review the official description and requirements before applying.

Compensation context

The listing states $84 / hour. Confirm the final rate, workload, and payment terms during the official application process.