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 who develop realistic, terminal-based scientific tasks for Terminal Bench Science. In this role, you will ensure that all tasks created by your team are physically accurate, reproducible, and reliable for grading. You will also provide coaching to maintain high standards and challenge levels in the tasks produced.

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 requiring genuine multi-step reasoning.
- Confirm that all tools, libraries, and dependencies are properly versioned and that results can be consistently reproduced.
- Validate dimensional consistency, unit systems, conservation laws, symmetries, integrator energy drift, convergence, and the statistical treatment of uncertainties.
- Verify that task tolerances reflect legitimate stochastic and numerical variations without allowing 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 manage task revisions through to completion.
- Onboard and mentor new trainers, fostering their growth and skill development.
- Allocate work effectively, 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 experience in physics.
- Strong programming skills in Python, C/C++, Julia, or Fortran, with proficiency in Linux environments.
- Hands-on experience in computational physics, simulation, or physics data analysis.
- Proven track record of reviewing code, analyses, or research outputs for quality and accuracy.
- Experience mentoring or leading small technical or research teams.
- Excellent written communication skills, particularly in providing precise and constructive feedback.

Preferred Qualifications and Benefits:
- Familiarity with scientific computing 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:
This is a contractor assignment requiring a commitment of at least 4 hours per day and a minimum of 40 hours per week, with a 4-hour overlap with Pacific Standard Time (PST). The contract duration is 4 weeks, with an expected start date as early as next week. Please note that this position does not include medical benefits or paid leave.