
Applied Physics
Alignerr · Seattle, WA
- Hybrid
- Contract
- $50,000 / year
- Seattle, WA
Job highlights
- Test AI models using physics expertise.
- Design complex physics problems for AI.
- Write expert solutions and audit AI.
- Provide feedback to refine AI behavior.
- Work remotely on high-impact projects.
About the role
Applied Physics AI Data Trainer
About The Role
What if your deep expertise in physics could directly shape how AI understands the fundamental laws of the universe? We're looking for PhD-level Applied Physicists to stress-test cutting-edge AI models — exposing gaps in their physical reasoning and helping ensure they never violate the principles of conservation of energy, momentum, or anything else your training tells you is non-negotiable.
This is a fully remote, flexible contract role built for researchers and scientists who want high-impact work on their own schedule. No prior AI experience required — just a command of physics that goes all the way down to first principles.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Design Advanced Physics Problems — Craft open-ended, multi-step problems at PhD qualifying exam level, spanning quantum mechanics, electrodynamics, thermodynamics, and classical mechanics
- Author Gold-Standard Solutions — Write rigorous, step-by-step "golden responses" with flawless handling of physical constants, unit conversions, and mathematical derivations
- Audit AI Reasoning — Evaluate AI-generated proofs and simulations for physical consistency, identifying where models hallucinate results or violate first principles
- Refine Model Behavior — Provide structured, expert feedback that improves how AI handles boundary conditions, conservation laws, and physics-informed constraints
- Document Failure Modes — Systematically record where and how AI reasoning breaks down so research teams can address root causes
Who You Are
- Completed or nearly completed PhD 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
- Uncompromising precision with units, scientific notation, and the logical structure of proofs
- Self-directed and reliable — comfortable working independently on technical tasks without hand-holding
- No prior AI or machine learning experience required
Nice to Have
- Experience with data annotation, scientific dataset evaluation, or quality assurance workflows
- Proficiency with tools like Python (NumPy/SciPy), MATLAB, or COMSOL
- Background in research publication, technical writing, or academic instruction
Why Join Us
- Work on some of the most technically demanding AI projects in existence alongside world-leading research labs
- Fully remote and asynchronous — work when and where it suits you
- Freelance autonomy with the structure of meaningful, high-value technical work
- Rare opportunity to apply your physics expertise beyond academia in a high-impact, forward-looking field
- Potential for ongoing work and contract extension as new projects launch
Key skills/competency
- Applied Physics
- AI Data Trainer
- PhD Physics
- Quantum Mechanics
- Electrodynamics
- Thermodynamics
- Classical Mechanics
- Mathematical Derivations
- Scientific Reasoning
- AI Auditing
Skills & topics
- Applied Physics
- AI Data Trainer
- Physics PhD
- Quantum Mechanics
- Electrodynamics
- Thermodynamics
- Classical Mechanics
- Scientific Reasoning
- AI Auditing
- Remote Contract
How to get hired
- Tailor your resume: Highlight your PhD research in physics and any experience with problem-solving or technical writing.
- Emphasize physics mastery: Showcase your deep understanding of classical mechanics, electrodynamics, thermodynamics, and quantum mechanics.
- Detail your precision: Provide examples of your meticulous handling of units, constants, and mathematical derivations.
- Showcase self-direction: Illustrate your ability to work independently on complex technical tasks.
Technical preparation
Master core physics principles thoroughly.,Practice solving complex, multi-step problems.,Develop rigorous mathematical derivation skills.,Refine precise handling of units/constants.
Behavioral questions
Describe a time you solved a complex physics problem.,How do you ensure accuracy in technical work?,Explain a difficult physics concept clearly.,How do you manage independent technical tasks?
Frequently asked questions
- What is the Applied Physics AI Data Trainer role at Alignerr about?
- The Applied Physics AI Data Trainer role at Alignerr involves leveraging your PhD-level physics expertise to test and improve AI models. You will design physics problems, author solutions, audit AI reasoning for physical consistency, and provide feedback to refine model behavior, ensuring AI adheres to fundamental scientific principles.
- Do I need prior AI or ML experience to apply for this role at Alignerr?
- No, prior AI or machine learning experience is not required for the Applied Physics AI Data Trainer position at Alignerr. The company is seeking individuals with a strong command of physics principles who can apply their knowledge to AI systems.
- What are the main physics disciplines required for the Applied Physics AI Data Trainer role?
- The Applied Physics AI Data Trainer role requires deep mastery across core physics pillars including Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics. You'll be designing problems and auditing AI reasoning within these domains.
- What is the work arrangement for the Applied Physics AI Data Trainer role at Alignerr?
- This is a fully remote and flexible contract role at Alignerr, allowing you to work on your own schedule. The commitment can range from 10 to 40 hours per week.
- How does Alignerr ensure AI models adhere to physics principles in this role?
- As an Applied Physics AI Data Trainer at Alignerr, you will audit AI reasoning, identify violations of first principles, and provide structured feedback to refine model behavior regarding boundary conditions, conservation laws, and physics-informed constraints.
- What kind of problems will I be designing as an Applied Physics AI Data Trainer at Alignerr?
- You will be designing advanced, open-ended, multi-step physics problems at a PhD qualifying exam level. These problems will span quantum mechanics, electrodynamics, thermodynamics, and classical mechanics, requiring rigorous solutions.