Domain Expert: Physics

About Turing:

Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality data, evaluations, and reinforcement learning environments that improve model capabilities in coding, reasoning, tool use, and multimodality. In coding, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across Financial Services, Life Sciences, Healthcare, Retail, Automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models.

Role Overview

We are hiring US-based academic physicists to contribute to the curation and evaluation of high-quality physics data for frontier AI models and research laboratories.

This is the Senior Reviewer track of the project. You will review complex physics problems and AI-generated solutions, resolve disagreements among reviewers, contribute to evaluation frameworks, and serve as a subject-matter advisor to client teams assessing AI model outputs.

This opportunity is designed for physics faculty and experienced researchers who want to apply their academic expertise to rigorous AI evaluation, scientific reasoning, and the development of reliable AI training infrastructure.

What You’ll Do Day-to-Day

• Conduct senior-level reviews of complex or ambiguous physics problems and AI-generated solutions.
• Evaluate answers for scientific accuracy, logical consistency, mathematical correctness, clarity, and adherence to instructions.
• Verify derivations, assumptions, calculations, units, notation, boundary conditions, and final conclusions.
• Identify factual errors, unsupported assumptions, invalid reasoning, and inconsistencies in model-generated content.
• Facilitate the structured resolution of disagreements among physics reviewers.
• Develop and refine evaluation rubrics, review guidelines, and quality standards.
• Provide expert advisory support to client teams reviewing AI model performance.
• Write technically rigorous, publication-quality explanations and reviewer feedback.
• Provide consultation within relevant physics specializations.
• Document review decisions and scientific consensus clearly and consistently.
• Follow project-specific protocols, confidentiality requirements, and quality standards.

Required Qualifications

• PhD in Physics, Applied Physics, or a closely related discipline from an accredited institution.
• Faculty appointment at the rank of Assistant Professor or above at an accredited US university or academic institution.
• At least three years of postdoctoral, faculty, or equivalent professional research experience.
• Active involvement in physics research, teaching, or academic supervision.
• Strong command of mathematical reasoning and advanced physics concepts.
• Demonstrated publication record in peer-reviewed physics or interdisciplinary scientific journals.
• Experience teaching undergraduate or graduate-level physics courses.
• Strong written communication skills and the ability to explain complex scientific reasoning clearly.
• Ability to evaluate multiple valid approaches to a physics problem and determine whether conclusions are scientifically defensible.
• Experience reviewing technical papers, research submissions, examination questions, or scientific content.
• Ability to lead and document expert consensus.
• Strong attention to detail and disciplined adherence to evaluation protocols.

Relevant Areas of Expertise

Expertise in one or more of the following areas is preferred:

• Classical mechanics
• Electromagnetism
• Thermodynamics and statistical mechanics
• Quantum mechanics and quantum information
• Optics and photonics
• Condensed matter physics
• Atomic, molecular, and optical physics
• Nuclear and particle physics
• Plasma physics
• Astrophysics and cosmology
• Computational physics
• Mathematical physics
• Materials science
• Biophysics
• Experimental physics and instrumentation

Preferred Qualifications

• Prior experience with AI evaluation, scientific data annotation, or large language model research.
• Experience developing scientific rubrics, benchmarks, or assessment frameworks.
• Familiarity with computational tools such as Python, MATLAB, Mathematica, Julia, or similar platforms.
• Experience with numerical modeling, simulations, or scientific computing.
• Prior journal peer-review or editorial experience.
• Service on research, academic, grant-review, or ethics committees.
• Experience mentoring graduate students, postdoctoral researchers, or junior faculty.
• Active participation in the American Physical Society or another recognized physics organization.
• Familiarity with evaluating AI-generated mathematical derivations and scientific explanations.

Performance Expectations

• Take senior-review responsibility for assigned case batches.
• Deliver scientifically accurate and defensible evaluations.
• Maintain consistent quality and reliability across assignments.
• Clearly document errors, assumptions, calculations, and final review decisions.
• Collaborate constructively with other faculty-level reviewers.
• Communicate professionally with client teams during advisory sessions.
• Meet agreed deadlines and project quality requirements.
• Maintain confidentiality and comply with all project protocols.

Conflict-of-Interest Disclosure

Applicants must disclose any active equity, advisory, consulting, research-funding, or paid relationships with:

• Artificial intelligence companies
• Scientific software or simulation companies
• Educational technology platforms
• Research laboratories or organizations whose work may appear in project content
• Other commercial entities relevant to assigned cases

Disclosed conflicts will not automatically disqualify an applicant but may be considered when assigning work.

Perks of Freelancing with Turing

• Competitive compensation and flexible remote work.
• Opportunity to learn how advanced AI systems are trained and evaluated.
• Work on cutting-edge projects with leading AI laboratories.
• Collaborate with researchers and experts from diverse scientific backgrounds.
• Potential for contract extension based on project needs and performance.
• Flexible, asynchronous work designed to complement academic responsibilities.