Materials Science, Semiconductor AI Expert

🔥 7 minutes ago

🌐 United States, United Kingdom – Remote

🇺🇸 United States – Remote 🇬🇧 United Kingdom – Remote

⏳ Contract/Temporary

🟡 Mid-level

🟠 Senior

🤖 Artificial Intelligence

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Gramian Consulting

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.

📋 Description

• 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 Atomic Layer Deposition (ALD), Chemical Vapor Deposition (CVD), Physical Vapor Deposition (PVD), plasma etching, Chemical Mechanical Planarization (CMP), 3D semiconductor packaging, or 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.