Applied Physics - AI Data Trainer at Alignerr

Position Applied Physics - AI Data Trainer
Posted 07 Jan 2026
Expired 06 Feb 2026
Company Alignerr
Location Queensland | AU
Job Type Full Time

Job Description:

Latest job information from Alignerr for the position of Applied Physics - AI Data Trainer. If the Applied Physics - AI Data Trainer vacancy in Queensland matches your qualifications, please submit your latest application or CV directly through the updated Jobkos job portal.

Please note that applying for a job may not always be easy, as new candidates must meet certain qualifications and requirements set by the company. We hope the career opportunity at Alignerr for the position of Applied Physics - AI Data Trainer below matches your qualifications.

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2 days ago. Be among the first 25 applicants.

Base pay range

$40.00/hr – $80.00/hr

Location: Remote

About The Job

At Alignerr, we partner with the world’s leading AI research teams and labs to build and train cutting‑edge AI models.

We are seeking PhD‑level Applied Physicists to challenge Large Language Models on their understanding of the physical world. You will work on university‑level and research‑level benchmarks in topics such as quantum mechanics, electromagnetism, and thermodynamics. Your goal is to document failure modes in AI reasoning so we can ensure models respect the fundamental laws of the universe, such as conservation of energy and momentum. Work on high‑impact projects while earning $40+/hour, fully remote, with flexible weekly hours.

Organization: Alignerr | Position: Applied Physics - AI Data Trainer | Type: Hourly Contract | Compensation: $40–$80 /hour | Location: Remote | Commitment: 10–40 hours/week

What You’ll Do
  • Develop Complex Problems: Design advanced, open‑ended physics problems (equivalent to PhD qualifying exams) that require multi‑step logical reasoning and mathematical derivation.
  • Author Ground‑Truth Solutions: Create "golden responses" that provide rigorous, step‑by‑step solutions, ensuring that every physical constant and unit conversion is perfect.
  • Technical Auditing: Evaluate AI‑generated simulations and proofs for physical consistency. Identify where a model "hallucinates" physics that violates first principles.
  • Refine Reasoning: Provide structured feedback to improve the model’s ability to perform "Physics‑Informed" reasoning, helping it understand constraints like boundary conditions and conservation laws.
Requirements
  • Advanced Degree: PhD (completed or in the final stages) in Applied Physics, Physics, or a closely related field (e.g., Engineering Physics).
  • Domain Expertise: Mastery of the core pillars of physics: Classical Mechanics, Electrodynamics, Statistical Mechanics, and Quantum Mechanics.
  • Analytical Writing: Exceptional ability to explain complex physical phenomena and mathematical derivations in clear, structured English.
  • Precision: An uncompromising eye for detail regarding units, scientific notation, and the logical flow of a proof.
  • No AI experience required.
Preferred
  • Prior experience with data annotation, data quality, or evaluation systems for scientific datasets.
  • Experience with tools such as MATLAB, COMSOL, or Python (NumPy/SciPy).
Why Join Us
  • Competitive pay and flexible remote work.
  • Collaborate with a team working on cutting‑edge AI projects.
  • Exposure to advanced LLMs and how they’re trained.
  • Freelance perks: autonomy, flexibility, and global collaboration.
  • Potential for contract extension.
Application Process (Takes 15‑20 min)
  1. Submit your resume.
  2. Complete a short screening.
  3. Project matching and onboarding.

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Seniority level

Internship

Employment type

Contract

Job function

Education and Training

Industries

Technology, Information and Internet #J-18808-Ljbffr

Job Info:

  • Company: Alignerr
  • Position: Applied Physics - AI Data Trainer
  • Work Location: Queensland
  • Country: AU

How to Submit an Application:

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