Applied Physics
Alignerr · Dallas, TX
- Hybrid
- Contract
- $60,000 / year
- Dallas, TX
Job highlights
- Train AI models using advanced physics knowledge.
- Design challenging physics problems for AI.
- Author rigorous, step-by-step physics solutions.
- Evaluate AI reasoning for scientific accuracy.
- Provide expert feedback to improve AI.
About the role
About The Role
What if your deep expertise in physics could directly shape how AI understands the physical world — ensuring it never violates conservation of energy, misapplies quantum mechanics, or hallucinates impossible thermodynamics?
We're looking for PhD-level Applied Physicists to stress-test and train cutting-edge Large Language Models on university and research-level physics. You'll design problems that expose the limits of AI reasoning, author rigorous solutions, and provide structured feedback that teaches models to think like a physicist.
This is a fully remote, flexible contract role. No prior AI or data annotation experience required — just a mastery of physics and an uncompromising eye for scientific rigour.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Problems — Craft PhD qualifying exam-level physics problems that demand multi-step logical reasoning, mathematical derivation, and deep conceptual understanding across subfields
- Author Gold-Standard Solutions — Write rigorous, step-by-step "golden responses" with perfect unit conversions, physical constants, and airtight logical flow
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models "hallucinate" physics that violates first principles
- Refine Model Behaviour — Provide structured, expert feedback that improves AI reasoning around boundary conditions, conservation laws, and physics-informed constraints
- Work Independently — Complete task-based assignments on your own schedule, fully asynchronously
Who You Are
- Holds a PhD (completed or near completion) in Applied Physics, Physics, Engineering Physics, or a closely related field
- Deep mastery across the core pillars: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics
- Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English
- Precision-focused — you notice when units are off, when a derivation skips a step, or when a physical argument breaks down
- Self-motivated and consistent when working independently
- No prior AI or machine learning experience required
Nice to Have
- Experience with scientific data annotation, data quality evaluation, or benchmark creation
- Proficiency with computational tools such as Python (NumPy/SciPy), MATLAB, or COMSOL
- Background spanning multiple physics subfields or interdisciplinary research areas
- Experience writing for technical audiences — papers, textbooks, or problem sets
Why Join Us
- Work on high-impact AI projects in collaboration with the world's leading AI research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, technically challenging work
- Apply your expertise to problems that genuinely matter — helping AI reason correctly about the physical universe
- Potential for ongoing work and contract extension as new projects launch
Key skills/competency
- Applied Physics PhD
- AI Data Training
- Large Language Models
- Physics Problem Design
- Scientific Rigour
- Classical Mechanics
- Electrodynamics
- Statistical Mechanics
- Quantum Mechanics
- AI Reasoning Evaluation
Skills & topics
- Applied Physics
- Physics
- AI
- Data Trainer
- Large Language Models
- PhD
- Remote
- Contract
- AI Ethics
- Scientific Rigor
How to get hired
- Tailor your resume: Highlight your PhD research and physics expertise. Emphasize problem-solving and analytical skills relevant to AI training.
- Showcase physics mastery: Detail your experience with Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics. Mention any publications or complex derivations.
- Demonstrate rigor: Provide examples of your attention to detail, especially in unit conversions and logical flow, as this is critical for AI model accuracy.
- Highlight independent work: Mention your ability to work autonomously and manage your schedule effectively, as this role is fully remote and asynchronous.
- Apply directly: Submit your application through the Alignerr careers portal, ensuring all requested documentation is included.
Technical preparation
Master core physics: mechanics, E&M, thermo, QM.,Practice complex multi-step problem derivation.,Ensure perfect unit conversions and constants.,Identify physical inconsistencies in arguments.
Behavioral questions
Describe a time you found a subtle error.,How do you ensure rigor in complex work?,How do you manage your own work schedule?,Explain a complex physics concept clearly.
Frequently asked questions
- What are the key physics areas required for the Applied Physics PhD AI Data Trainer role at Alignerr?
- The Applied Physics PhD AI Data Trainer role at Alignerr requires deep mastery across Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics. Your PhD should be in Applied Physics, Physics, Engineering Physics, or a closely related field.
- Is prior AI or machine learning experience necessary for the Alignerr Applied Physics PhD AI Data Trainer position?
- No, prior AI or machine learning experience is not required for this role. Alignerr values your deep physics expertise and scientific rigor above all else for this Applied Physics PhD AI Data Trainer position.
- What is the work arrangement for the Applied Physics PhD AI Data Trainer at Alignerr?
- The Applied Physics PhD AI Data Trainer position at Alignerr is a fully remote, flexible contract role. You can complete task-based assignments on your own schedule, working fully asynchronously.
- What kind of problems will I be designing as an Applied Physics PhD AI Data Trainer for Alignerr?
- As an Applied Physics PhD AI Data Trainer for Alignerr, you will design PhD qualifying exam-level physics problems. These problems will demand multi-step logical reasoning, mathematical derivation, and deep conceptual understanding across various physics subfields to stress-test AI models.
- How does Alignerr ensure scientific accuracy in AI models through this role?
- Alignerr uses Applied Physics PhDs to audit AI reasoning for physical consistency, identifying 'hallucinations' that violate first principles. You will also refine model behavior by providing structured feedback on boundary conditions and conservation laws.
- What are the expected work hours for the Applied Physics PhD AI Data Trainer role?
- The commitment for the Applied Physics PhD AI Data Trainer role at Alignerr is flexible, ranging from 10 to 40 hours per week. You can complete your task-based assignments on your own schedule, fully asynchronously.
- What is the benefit of joining Alignerr as an Applied Physics PhD AI Data Trainer?
- Joining Alignerr as an Applied Physics PhD AI Data Trainer allows you to work on high-impact AI projects with leading AI research labs. It offers fully remote and flexible work, freelance autonomy, and the chance to apply your physics expertise to ensure AI reasons correctly about the physical universe.