Remote Pod Lead - Physics

Turing is a rapidly growing AI company focused on advancing and deploying cutting-edge AI systems. The company collaborates with leading AI labs to push the boundaries of model capabilities in areas such as reasoning, coding, multimodality, and STEM knowledge. These advancements are then applied to develop real-world AI solutions that address critical business challenges.

We are looking for an experienced Physics expert to lead a team of trainers responsible for creating realistic, terminal-based scientific tasks for Terminal Bench Science. In this role, you will ensure the physical accuracy, reproducibility, and reliability of every task produced by your team. You will also provide coaching to maintain high standards and foster continuous improvement in task quality.

Key Responsibilities:
- Review trainer-created tasks comprehensively, including task statements, datasets, simulation inputs, environments, reference solutions, and automated tests.
- Ensure tasks represent authentic physics workflows and require genuine multi-step reasoning.
- Verify that tools, libraries, and dependencies are properly pinned to guarantee reproducibility.
- Validate dimensional consistency, unit systems, conservation laws, symmetries, integrator energy drift, convergence, and the statistical treatment of uncertainties.
- Confirm that tolerance levels reflect legitimate stochastic and numerical variations without accepting physically incorrect results.
- Ensure graders assess observables, fitted parameters, uncertainties, or physical invariants rather than superficial formatting.
- Prevent tasks from being gamed through hard-coded outputs or bypassed computations.
- Provide clear, actionable written feedback and track revisions until completion.
- Onboard and mentor new trainers to build team capability.
- Allocate work, monitor quality and throughput, and escalate any blockers promptly.
- Maintain comprehensive pod documentation, including guidelines, recurring issues, and examples of exemplary tasks.

Required Qualifications:
- Ph.D., postdoctoral experience, or equivalent advanced expertise in physics.
- Strong programming skills in Python, C/C++, Julia, or Fortran, with proficiency in Linux environments.
- Practical experience in computational physics, simulations, or physics data analysis.
- Demonstrated ability to review code, analyses, or research outputs critically.
- Experience mentoring or leading small technical or research teams.
- Excellent written communication skills, particularly in delivering precise and constructive feedback.

Preferred Qualifications and Benefits:
- Familiarity with scientific and physics-related tools such as QuTiP, Qiskit, Kwant, ITensor, ROOT, Geant4, Astropy, Dedalus, or MEEP.
- Experience with Docker, Git, continuous integration systems, and automated testing frameworks.
- Background in designing benchmarks or simulation-based evaluations.
- Bonus points for experience evaluating AI coding or terminal agents, working in large collaborations with formal review processes, or prior involvement in AI training or evaluation programs.

Offer Details:
- Commitment of at least 4 hours per day, totaling a minimum of 40 hours per week, with at least 4 hours overlapping Pacific Standard Time (PST).
- Contractor assignment without medical or paid leave benefits.
- Initial contract duration of 4 weeks, with an expected start date in the near term.

This role offers a unique opportunity to apply your physics expertise in a cutting-edge AI environment, leading a specialized team to develop scientifically rigorous tasks that advance AI capabilities.