Disclaimer: Links on this site are referral links and I may earn a fee from Mercor or Micro1 if you click them. I do not work for Micro1 or Mercor.

Physics Remote Jobs

Physics & Science AI Training Roles — Mercor via Applied Clinical Judgement
Applied Clinical Judgement Physics & Science AI Roles Via Mercor
Referral eligibility
Building…

Physics & Science AI Training Roles

Mercor is recruiting physicists, astronomers, and related scientists to help train and evaluate frontier AI models. These are remote, flexible contract opportunities paying $60–$90 per hour. Applied Clinical Judgement is introducing qualified candidates to Mercor through Mercor’s referral programme.

All roles are with Mercor (mercor.com), not with ACJ. ACJ earns a referral fee if you are successfully placed — this does not affect your pay, your application, or Mercor’s hiring decisions. You apply directly to Mercor. ACJ has no role in whether you are accepted, but can support you in the application process if you accept a referral. We can also vouch for the best match candidates — if you score highly you’ll see a vouch option appear offering a free 15 minute informal chat.

🔬

Problem Writing & Evaluation

Create original Olympiad-level physics or astronomy problems designed to challenge frontier AI models. Identify logical flaws and failures in AI-generated solutions.

🧮

LaTeX Proficiency Required

All problem-writing roles require high LaTeX proficiency for formatting problems and solutions. Chain-of-thought reasoning and rigorous derivations are expected.

📍

Remote & Flexible

Work on your own schedule, typically 20–40 hrs/week. Some roles are restricted to US/UK/Canada/EU graduates. Initial terms are ~2 months with extension potential.

Before applying: H1-B or STEM OPT candidates may be suitable for similar/other roles. Please check Mercor.com directly if you are an H1-B or STEM OPT candidate. Read the adverts carefully for country of residence requirements — usually USA, Canada, UK, EU unless otherwise stated. Also check carefully the minimum hours commitment.

Mercor seeks Physics PhDs specialising in Advanced Quantum Mechanics, Advanced Electrodynamics, or Advanced Classical Mechanics for a premier project with one of the world’s top AI labs. You will contribute deep subject matter expertise to a cutting-edge AI training project involving state-of-the-art large language models, specifically by generating difficult, domain-specific problems that current frontier models struggle to solve correctly. The work is problem-writing and quality evaluation rather than annotation — you are the expert, not the reviewer. Tasks run at 4–6 per week, each taking several hours, requiring rigorous physics expertise and the ability to follow complex instructions precisely. Your contributions directly inform the training data shaping the next generation of AI systems. This is a fully remote, ongoing role starting in February with rolling applications. Experts are expected to contribute consistently over the project term.

Key requirementsPhD in Physics with specialisation in Advanced Quantum Mechanics, Advanced Electrodynamics, or Advanced Classical Mechanics. Graduate degree from US, UK, Canada, or Western Europe — this role is geography-restricted and UK-based applicants are eligible. High attention to detail. Exceptional written and verbal communication skills in English. Strong proficiency in English required throughout. LaTeX proficiency required for problem formatting. Note: the screening process involves a short AI interview and form, taking approximately 20–40 minutes in total.

Quick fit check — 8 questions

1. Your qualification and research background

2. How would you rate your LaTeX proficiency?

3. Your written English

4. Weekly availability for this project

5. Country of residence

6. How current is your engagement with your specialism?

7. Specialism alignment with this role

8. Research influence and seniority

Mercor seeks Physics PhDs specialising in Statistical Mechanics, Condensed Matter Physics, or Atomic, Molecular and Optical (AMO) Physics for a premier AI training project with one of the world’s leading AI labs. You will contribute deep domain expertise by generating difficult, high-quality problems in your specialism — the kind that expose genuine reasoning failures in frontier AI models. This is not annotation work; it requires the ability to construct challenging, original problems and evaluate solutions with the rigour expected at a peer-review level. Tasks run at 4–6 per week, each requiring several hours of focused expert effort. The work requires rigorous physics expertise and an ability to follow complex instructions precisely, including formatting requirements. Your contributions help create training data that will directly shape the quality of next-generation AI reasoning in your field. The role is ongoing from February with rolling applications and a fully remote structure.

Key requirementsPhD in Physics with specialisation in Statistical Mechanics, Condensed Matter Physics, or Atomic, Molecular and Optical (AMO) Physics. Graduate degree from US, UK, Canada, or Western Europe — geography-restricted, UK-based applicants are eligible. Exceptional written English. High attention to detail. LaTeX proficiency required. Screening involves a short AI interview and form, approximately 20–40 minutes total. Minimum 20 hrs/week commitment expected.

Quick fit check — 8 questions

1. Your qualification and research background

2. How would you rate your LaTeX proficiency?

3. Your written English

4. Weekly availability for this project

5. Country of residence

6. How current is your engagement with your specialism?

7. Specialism alignment with this role

8. Research influence and seniority

This role focuses on evaluating and improving how AI models explain, reason about, and respond to physics questions across both foundational and advanced topics. Unlike the problem-writing roles above, the emphasis here is on assessing the quality of AI outputs rather than generating adversarial problems from scratch. You will write and refine prompts designed to guide model behaviour in physics contexts, evaluate LLM-generated responses for conceptual accuracy, mathematical correctness, and reasoning quality, conduct fact-checking using authoritative sources, and annotate model outputs by identifying strengths, inaccuracies, and areas for improvement. You will also assess clarity, structure, and appropriateness of explanations for different audience levels, and apply consistent evaluation standards using detailed rubrics and taxonomies. This role is broader in scope than pure problem-writing and is particularly well suited to physicists who are strong written communicators, have significant hands-on LLM experience, and are comfortable working to structured evaluation frameworks. Location is restricted to US, UK, and Canada — UK-based applicants are eligible.

Key requirementsPhD in Physics or a closely related field. Deep expertise in one or more sub-domains: Classical Mechanics and Dynamics, Quantum Physics, Relativity, Cosmology, or High-Energy Physics. Significant experience using large language models is essential — you must understand how and why people use them. Excellent written English with the ability to explain complex physics concepts clearly. Strong attention to detail. Demonstrated experience reviewing or editing technical or academic writing. Prior experience with RLHF, model evaluation, or data annotation is advantageous. Location restricted to US, UK, or Canada.

Quick fit check — 7 questions

1. Your qualification and research background

2. How would you rate your LaTeX proficiency?

3. Your written English

4. Weekly availability for this project

5. Country of residence

6. How much experience do you have using large language models (ChatGPT, Claude, Gemini etc.)?

7. Prior AI evaluation, annotation, or RLHF experience

This is not a specific project posting — it is an open application to join Mercor’s Physicist Expert Network. By applying here, you enter the pool from which Mercor matches physicists to AI training projects as they become available. The advantage of the talent network is flexibility: you apply once, complete your profile and pass an AI interview, and Mercor then invites you to interview for specific opportunities that match your expertise and schedule preferences, rather than requiring you to apply role by role. Projects in the network span a wide range of physics sub-disciplines and task types — from problem-writing and solution evaluation to prompt engineering and model annotation. Typical project commitments run from 15 to 30 hours per week. Payments are processed weekly via Stripe or Wise. If you hold physics expertise but are uncertain which specific role above best fits your background, or if none of the listed roles precisely matches your specialism, the talent network is the most practical entry point. It is also a good option if your schedule availability is variable and you want to be considered for shorter or part-time project engagements as they arise.

Key requirementsProfessional experience in one or more of: theoretical or computational modelling, experimental design and data analysis, scientific programming, or domain-specific physics research. Strong written communication skills in English. Ability to work independently and reliably in a remote environment. No specific geography restriction applies to the talent network itself, though individual projects within it may carry location requirements. No H1-B or STEM OPT support at this time — check Mercor.com directly if this applies to you.

Quick fit check — 7 questions

1. Your qualification and research background

2. How would you rate your LaTeX proficiency?

3. Your written English

4. Weekly availability for this project

5. Country of residence

6. Your physics expertise breadth

7. Comfort with variable, project-based scheduling

Mercor seeks Physics PhDs specialising in General Relativity, Astrophysics, or Cosmology for a premier project with one of the world’s top AI labs. You will contribute deep subject matter expertise to a cutting-edge AI training project involving state-of-the-art large language models, specifically by generating difficult, domain-specific problems that current frontier models struggle to solve correctly. The work is problem-writing and quality evaluation rather than annotation — you are the expert, not the reviewer. Tasks run at 4–6 per week, each taking several hours, requiring rigorous physics expertise and the ability to follow complex instructions precisely. Your contributions directly inform the training data shaping the next generation of AI systems. This is a fully remote, ongoing role starting in February with rolling applications.

Key requirementsPhD in Physics with specialisation in General Relativity, Astrophysics, or Cosmology. Graduate degree from US, UK, Canada, or Western Europe — this role is geography-restricted and UK-based applicants are eligible. High attention to detail. Exceptional written and verbal communication skills in English. LaTeX proficiency required. Screening involves a short AI interview and form, approximately 20–40 minutes total.

Quick fit check — 8 questions

1. Your qualification and research background

2. How would you rate your LaTeX proficiency?

3. Your written English

4. Weekly availability for this project

5. Country of residence

6. How current is your engagement with your specialism?

7. Specialism alignment with this role

8. Research influence and seniority

Due for review at 10:46am on Sunday March 14th, 2027

Last Reviewed: