Applied Physics Specialist

Montreal, Quebec, Canada
Remote
Posted Oct 16, 2026
1 position

US$40–US$80 / hour

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Employment type: Contract
Experience level: Senior · 5+ years
Minimum education: Master’s degree
Posting language: English
Working hours: 40 hours per week
Location requirements: Country, Montreal, Quebec, Canada
Seniority: Mid-Senior level

Job summary

Design advanced physics problems and write rigorous, step-by-step solutions to serve as benchmarks for AI training. Evaluate AI-generated reasoning for physical accuracy and provide structured feedback to improve models’ understanding of physics principles.

Job details

Applied Physics Specialist (AI Training) About The Role What if your deep expertise in physics could directly shape how AI reasons about the physical world — ensuring it respects the fundamental laws that govern everything from quantum particles to electromagnetic fields? We're looking for PhD-level Applied Physicists to stress-test and refine cutting-edge Large Language Models on their understanding of physics. You'll craft expert-level problems, author rigorous solutions, and identify exactly where AI reasoning breaks down — helping build models that truly understand the universe, not just approximate it. This is a fully remote, flexible contract role. No prior AI experience required — just world-class physics knowledge and the precision to match. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: 10–40 hours/week What You'll Do Design Expert-Level Problems — Craft advanced, open-ended physics problems equivalent to PhD qualifying exams, requiring multi-step logical reasoning and rigorous mathematical derivation Author Gold-Standard Solutions — Write definitive, step-by-step solutions with flawless physical constants, unit conversions, and logical flow — the benchmark the AI is trained against Audit AI Reasoning — Evaluate AI-generated proofs, simulations, and explanations for physical consistency, identifying where models "hallucinate" physics that violates first principles Refine Model Behaviour — Provide structured, expert feedback that helps AI better understand constraints like boundary conditions, conservation laws, and symmetry principles Work Across Core Domains — Engage with topics spanning quantum mechanics, electrodynamics, thermodynamics, classical mechanics, and more at research and university level Who You Are Holds a PhD (completed or near-final stages) in Applied Physics, Physics, Engineering Physics, or a closely related field Deep mastery across the core pillars of physics: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics Exceptional analytical writing skills — able to explain complex physical phenomena and mathematical derivations in clear, structured English Uncompromising precision with units, scientific notation, dimensional analysis, and the logical structure of a proof Self-motivated and reliable when working independently on technical tasks No prior AI or data annotation experience required Nice to Have Experience with scientific computing tools such as MATLAB, COMSOL, or Python (NumPy/SciPy) Prior involvement in data annotation, dataset quality review, or evaluation of scientific content Research background in computational physics, materials science, optics, or related applied fields Familiarity with AI tools or language models as an end user Why Join Us Work on some of the most technically demanding AI projects in the world alongside leading research labs Fully remote and flexible — design your own schedule and work from anywhere Freelance autonomy with meaningful, intellectually stimulating work that draws on your deepest expertise Make a tangible impact on how AI understands and reasons about the physical world Potential for ongoing work and contract extension as new projects launch

What you’ll do

Requirements

A completed or near-final PhD in Applied Physics, Physics, Engineering Physics, or a closely related field is required, along with deep knowledge of core physics domains. Candidates should have exceptional analytical writing skills, precision with units and mathematical reasoning, and the ability to work independently; prior AI experience is not required.