Semiconductor Materials Expert (AI Training)
Confirmed on the employer's own hiring board on Sep 24, 2026. First seen by Alion on Sep 23, 2026. Gramian Consulting Group scores A on the Alion truth index.
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are seeking an experienced Materials Science or Semiconductor Physics Expert to evaluate and benchmark advanced AI models against real-world materials discovery workflows. You will collaborate with client R&D teams to transform atomic-scale engineering challenges into structured, verifiable test scenarios, define scientific grading criteria, and diagnose AI model performance.
The ideal candidate combines deep expertise in semiconductor materials, thin-film processes, and computational physics with the ability to translate complex scientific problems into reproducible evaluation workflows.
LOCATION: Remote - United States (excluding specified states) and United Kingdom.
Excluded States:
- Texas
- Illinois
- California
- Connecticut
- Massachusetts
- New Jersey
- Vermont
Key Responsibilities
Participate in technical discovery sessions with client R&D teams.
Map and deconstruct end-to-end materials discovery workflows into discrete subprocesses.
Convert real-world materials engineering challenges into structured test scenarios.
Define inputs, constraints, expected outputs, and verified golden reference solutions.
Develop scientific scoring rubrics and programmatic validation rules.
Validate criteria such as stoichiometry, thermodynamics, and simulation stability.
Inspect step-by-step AI reasoning traces to identify failure patterns and root causes.
Distinguish scientific errors from incorrect assumptions, implementation issues, or evaluation defects.
Define domain-specific data generation requirements and synthetic physics pipelines.
Contribute to discussions on fine-tuning strategies and methods for improving AI model performance.
Communicate technical findings and recommendations during client workshops.
Requirements
- Deep technical expertise in atomic-scale materials engineering or semiconductor technologies.
Hands-on experience with one or more of the following:
Atomic Layer Deposition (ALD)
Chemical Vapor Deposition (CVD)
Physical Vapor Deposition (PVD)
Plasma etching
Chemical Mechanical Planarization (CMP)
3D semiconductor packaging
Advanced memory or logic architectures
Familiarity with computational physics or chemistry modeling workflows, including DFT, MD, or kMC.
Ability to formulate complex, open-ended scientific workflows into structured and verifiable problem statements.
Experience defining scientific ground-truth criteria, validation methods, or evaluation frameworks.
Strong verbal and written English communication skills for technical and business workshops.