Applied Physics Specialist

About the Role

This opportunity is for a PhD-level applied physicist to help improve how large language models handle physical reasoning. The work focuses on building challenging physics problems, checking AI outputs for scientific accuracy, and supplying expert feedback so models better reflect real-world laws and constraints.

The role is remote, flexible, and contract-based, making it suitable for researchers and subject-matter experts who want to contribute on their own schedule. Prior AI experience is not required; the key requirement is strong physics expertise and the ability to spot weak or incorrect reasoning.

Role Details

• Organization: Alignerr
• Engagement type: Hourly contract
• Location: Remote
• Weekly commitment: 10 to 40 hours per week

What You Will Do

• Create demanding physics problems at a doctoral level that require multi-step reasoning, mathematical derivation, and deep conceptual understanding across areas such as quantum mechanics, electromagnetism, and thermodynamics.
• Develop accurate reference solutions that clearly show each step and keep constants, units, and logic fully correct.
• Review AI-generated answers, proofs, and simulations to check whether they remain physically valid and whether they violate core principles such as conservation of energy or momentum.
• Share structured expert feedback that helps improve how the model handles physics-based reasoning, boundary conditions, and practical physical limits.
• Record recurring error patterns and reasoning failures so research teams can address the underlying issues.

Requirements

• A completed or near-complete PhD in Applied Physics, Physics, Engineering Physics, or a closely related field.
• Strong mastery of key physics foundations, including classical mechanics, electrodynamics, statistical mechanics, and quantum mechanics.
• Ability to explain complex scientific ideas and mathematical derivations in clear, well-organized written English.
• Careful attention to units, scientific notation, dimensional analysis, and logical consistency in derivations.
• Comfort working independently and staying dependable on technical assignments.
• No previous experience in AI or data annotation is needed.

Nice to Have

• Experience with data annotation, scientific dataset review, or quality assurance for research material.
• Working knowledge of Python, including NumPy and SciPy, MATLAB, or COMSOL.
• Experience designing academic assessments or research benchmarks.
• Background in writing or reviewing technical content for educational or research use.

Why Join

• Contribute to advanced AI projects alongside leading research teams.
• Enjoy fully remote work with flexible scheduling.
• Keep the independence of freelance-style work while doing intellectually meaningful projects.
• Influence how AI systems understand and reason about the physical world.
• Gain exposure to frontier LLM development and model evaluation workflows.
• There may be ongoing work and contract renewals as new projects begin.