Applied Physics Specialist
Alignerr
Delhi, Delhi, India2h agovia LinkedIn
About the Role
Alignerr is seeking PhD-level Applied Physicists for a fully remote, flexible contract role. The position focuses on stress-testing and improving AI models by probing their understanding of the physical world. No prior AI experience is required; deep domain expertise is paramount.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems: Craft PhD-level, open-ended physics problems requiring multi-step logical reasoning, rigorous mathematical derivation, and mastery of first principles.
- Author Ground-Truth Solutions: Write precise, step-by-step "golden responses," verifying every constant, unit conversion, and logical step.
- Audit AI Reasoning: Evaluate AI-generated proofs and simulations for physical consistency, identifying areas where models "hallucinate" physics that violates fundamental laws.
- Refine Model Behaviour: Provide structured, expert feedback to improve AI reasoning around boundary conditions, conservation laws, and physics-informed constraints.
- Push the Boundaries: Work on university-level and research-level benchmarks across quantum mechanics, classical mechanics, electromagnetism, statistical mechanics, and more.
Requirements & Tech Stack
- PhD completed or in final stages in Applied Physics, Physics, Engineering Physics, or a closely related field.
- Deep mastery of core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics.
- Exceptional analytical writing ability to explain complex derivations and physical phenomena clearly and structurally.
- Uncompromising precision with units, scientific notation, and the logical flow of a proof.
- Self-motivated and consistent when working independently.
- No prior AI or data annotation experience required.
Nice to Have:
- Experience with data annotation, data quality, or evaluation workflows for scientific datasets.
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL.
- Background in research publication, academic instruction, or technical writing.