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Remote Pod Lead Math
Job Location:
Hourly Salary:
Posted:
24 October 2026 (21 hours ago)
Posted:
Application Deadline:
21 January 2027
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
About Turing:
Turing is one of the worlds fastest-growing AI companies accelerating the advancement and deployment of powerful AI systems.
Turing helps customers in two ways: Working with the worlds 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 Mathematics expert to lead a pod of 510 trainers developing realistic terminal-based scientific and technical tasks for Terminal Bench Science.
- You will review trainer-created tasks for mathematical correctness reproducibility challenge and grader reliability. You will also mentor trainers manage quality and throughput and ensure that tasks reflect authentic mathematical research and computational workflows.
- The role covers numerical and applied mathematics scientific computing optimization statistics mathematical modeling computational algebra and formal verification.
What youll do:
- Review tasks end to end including problem statements datasets environments reference solutions and automated tests.
- Verify mathematical correctness well-posedness convergence stability conditioning discretization error and edge-case handling.
- Ensure tasks require genuine multi-step reasoning rather than lookup or a single library call.
- Validate that exact symbolic arbitrary-precision or floating-point computation is used appropriately.
- Check that tolerances are suitable for the problems numerical conditioning.
- Design and review graders based on mathematical properties such as residuals feasibility optimality certificates invariants error bounds or proof checking.
- Ensure tasks are reproducible through pinned tools libraries solver versions and dependencies.
- Identify and prevent hard-coded solutions test-file leakage and other methods of bypassing the intended computation.
- Provide precise actionable feedback and track trainer revisions through closure.
- Mentor and onboard trainers on mathematical rigor task design coding practices and evaluation standards.
- Allocate work monitor quality and throughput and escalate blockers.
- Maintain pod documentation covering guidelines recurring issues and exemplary tasks.
- Collaborate with the Mathematics Team Lead and other technical stakeholders to improve benchmark quality.
What were looking for:
- Ph.D. postdoctoral experience or equivalent advanced experience in mathematics applied mathematics statistics or a related field.
- Strong programming skills in Python Julia C/C MATLAB/Octave or a computer algebra system.
- Strong Linux and terminal proficiency.
- Hands-on experience with numerical methods scientific computing symbolic computation optimization computational statistics or mathematical modeling.
- Ability to rigorously evaluate mathematical derivations algorithms proofs and computational results.
- Experience reviewing research outputs code mathematical work or scientific workflows.
- Experience mentoring or leading small technical or research teams.
- Strong written communication and the ability to provide precise constructive feedback.
- Ability to assess reproducibility test reliability and the scientific validity of computational tasks.
Nice to have:
- Experience with NumPy SciPy SymPy mpmath SageMath PARI/GP GAP Macaulay2 or Mathematica-like workflows.
- Experience with FEniCS Firedrake PETSc or similar ODE/PDE tools.
- Experience with CVXPY JuMP Pyomo HiGHS or other optimization frameworks.
- Familiarity with Lean/mathlib Coq/Rocq Isabelle or other proof assistants.
- Experience with Docker Git CI systems and automated testing.
- Experience designing benchmarks competition problems or computational evaluations.
- Experience evaluating AI coding reasoning or terminal agents.
- Experience setting or judging mathematics olympiad or competition problems.
- Publications or open-source contributions in computational mathematics numerical software or formalized mathematics.
- Prior experience in AI training data generation or model 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
About Company
Build GenAI and other enterprise applications, train and enhance LLMs, or hire on-demand technical professionals with Turing.
