Remote Pod Lead - Physics
About Turing: Turing is one of the world’s fastest-growing AI companies, accelerating the advancement and deployment of powerful AI systems. Turing helps customers in two ways: Working with the world’s leading AI labs to advance frontier model capabilities in thinking, reasoning, coding, agentic behavior, multimodality, multilinguality, STEM and frontier knowledge; and leveraging that work to build real-world AI systems that solve mission-critical priorities for companies. Role Overview: We are seeking an experienced Physics expert to lead a pod of trainers building realistic, terminal-based scientific tasks for Terminal Bench Science. You will review every task your trainers produce for physical correctness, reproducibility, and grader reliability, and coach trainers to consistently deliver high-quality, challenging tasks. What you'll do: - Review trainer tasks end to end, including task statements, datasets, simulation inputs, environments, reference solutions, and automated tests. - Verify that tasks reflect authentic physics workflows and require genuine multi-step reasoning. - Check that tools, libraries, and dependencies are pinned and that results are reproducible. - Validate dimensional consistency, unit systems and conventions, conservation laws, symmetries, integrator energy drift, convergence, and statistical treatment of uncertainties. - Ensure tolerances reflect legitimate stochastic and numerical variation without accepting physically incorrect results. - Ensure graders verify observables, fitted parameters, uncertainties, or physical invariants rather than formatting. - Ensure tasks cannot be gamed through hard-coded outputs or bypassed computation. - Provide clear, actionable written feedback and track revisions through closure. - Onboard and mentor trainers. - Allocate work, track quality and throughput, and escalate blockers. - Maintain pod documentation covering guidelines, recurring issues, and exemplary tasks. What we're looking for: - Ph.D., postdoctoral experience, or equivalent advanced experience in physics. - Strong programming skills in Python, C/C++, Julia, or Fortran, with Linux proficiency. - Hands-on experience with computational physics, simulation, or physics data analysis. - Proven experience reviewing code, analyses, or research outputs. - Experience mentoring or leading small technical or research teams. - Excellent written communication skills for providing precise, constructive feedback Preferred Qualifications: - Familiarity with QuTiP, Qiskit, Kwant, ITensor, ROOT, Geant4, Astropy, Dedalus, MEEP, or similar tools. - Familiarity with Docker, Git, CI systems, and automated testing. - Experience designing benchmarks or simulation-based evaluations. Bonus Points: - Experience evaluating AI coding or terminal agents. - Experience working in large collaborations with formal internal review processes. - Prior experience in AI training or evaluation programs. Offer Details: - Commitments Required: At least 4 hours per day and minimum 40 hours per week with overlap of 4 hours with PST. - Employment type : Contractor assignment (no medical/paid leave) - Duration of contract : 4 week [expected start date is next week]