Remote Physics Expert (PhD)

Role Overview: We are seeking PhD-level Physics experts to contribute to cutting-edge AI research. As a Physics Expert – AI Trainer, you’ll design challenging problems, evaluate model outputs, and provide expert feedback to improve the reasoning capabilities of large language models (LLMs). This is a remote, contract-based role with flexible weekly hour options (10, 20, or 30 hours per week).

Key Responsibilities: Design and solve advanced physics problems across mechanics, electromagnetism, thermodynamics, quantum theory, and related domains. Evaluate AI-generated solutions for scientific rigor, correctness, and clarity. Provide structured, expert-level feedback that identifies model strengths, weaknesses, and misconceptions. Collaborate with AI researchers to refine evaluation benchmarks and improve training workflows. Contribute to the creation of physics-focused datasets that shape the frontier of AI performance.

Key Qualifications: PhD or Postdoctoral (or currently enrolled) in Physics, Applied Physics, or closely related fields. Strong analytical skills and ability to solve complex, multi-step problems with clear reasoning. Excellent written communication; able to explain advanced concepts simply and precisely. Independent, detail-oriented, and comfortable working in a remote research environment. Reliable technical setup (computer + internet). Why Join Turing? Impact: Your expertise will directly influence how the world’s most advanced AI systems understand and reason about physics. Flexibility: Remote-first role with weekly hour options tailored to your schedule. Collaboration: Work alongside global experts and leading AI labs. Career Growth: Gain exposure to cutting-edge AI research and future-proof your career at the intersection of physics and artificial intelligence.

Compensation: $50–$150 per hour, based on skills and experience. (paid once every two weeks).

Duration: 1 week to 3 months (project-based; extension possible).

Hours: Up to 30 hrs/week. Time Zone: 2–5 hrs/day overlap with UTC-8 (America/Los_Angeles), confirmed near onboarding. Selection Task-based assessment for shortlisted candidates → contract offer.