AI training contract
Principal Research Scientist (Computer Science / Computational Physics)
Science & Research · USD 100-400 an hour. · 4 openings
Principal Research Scientist (Computer Science / Computational Physics) is contract work for micro1, reviewing and correcting what AI models produce in science & research. The output of the job is expert judgement written down: a model gives an answer, someone who knows the subject decides whether it is right and explains why.
What it requires. No credential is stated on this listing beyond experience in the field.
What it pays. USD 100 to USD 400 an hour, as published by micro1. Rates in this category track how rare the credential is rather than how hard the work is.
Where. The listing says this role is remote and names no country. micro1 says it hires talent from around the world, except people who reside in Afghanistan, Belarus, China, Cuba, Democratic Republic of the Congo, Hong Kong, Iran, Iraq, Libya, Macao, Myanmar, North Korea, Russian Federation, Somalia, South Sudan, Sudan, Syria, Venezuela, Ukraine, Yemen, and Ethiopia. So this page lists every other country as eligible, on the strength of that rule and not of anything this listing says. Requirements can still differ by role, so check the application page on micro1 before you apply.
micro1 lists 4 openings on this role.
Skills named: Novelty judgment, Research direction, Computational rigor, Complex problem solving - Research.
Applications are made on micro1, not here. WFA Digital is independent of micro1 and may receive a referral fee if you are hired, at no cost to you.
Full listing, as published by micro1
Role Title: Principal Research Scientist (Computer Science / Computational Physics) Role Type: Contractor (flexible, Part-Time or Full-Time) Location: Remote micro1 is engaging Principal Research Scientist (Computer Science / Computational Physics)s to contribute to an advanced customer project at the intersection of computational theory and AI. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. You will work with frontier AI models and agents to tackle open problems, drive research direction, and define standards for scientific breakthroughs. Your insights and rigorous approach will be pivotal in charting what counts as genuine progress within your subfield. Scope of Work Identify, frame, and articulate foundational open problems, theoretical bounds, or simulation challenges where verifiable progress can be demonstrated. Guide AI models and agents in multi-step research processes—ranging from proofs and algorithms to numerical experiments and high-performance simulations. Critically assess and validate results, utilizing proof checks, computational reproduction, and formal methods to pinpoint the limits of model-generated reasoning. Evaluate and document the novelty, correctness, and significance of research outputs relative to current literature and established results. Produce clear, concise research memos detailing research attempts, partial solutions, and observed model limitations or failure patterns. Advise on research directions, recommending promising subfields and open problems suitable for advancement via AI models and computational tools. Preferred Qualifications 7 - 10+ years of active research in computer science or mathematical/computational physics, with a strong record of scholarly contributions. Recognition at the field level—such as major prizes, society fellowships, or plenary/invited talks at top scholarly events. A consistent publication record in leading venues within your domain, with recent results published in the past year. Demonstrated success resolving named open problems or introducing influential concepts adopted by peers. Deep, hands-on experience with computational research methods: simulation, numerical analysis, algorithmic implementation, and/or high-performance computing environments. Proven ability to rigorously examine technical work outside your immediate area of expertise. Experience on program committees, editorial boards, or with formal research tools (e.g., Lean, Coq, SAT/SMT solvers) is a strong plus, as is a public record of outlining open problems or showcasing research with advanced AI systems.
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Rate, openings and requirements checked 2026-10-19 against micro1's own public postings.