Remote Pod Lead - Math

Turing, one of the world’s fastest-growing AI companies, is advancing the development and deployment of powerful 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 create real-world AI solutions that address critical business challenges. Turing is currently seeking an experienced Mathematics expert to lead a team of 5–10 trainers focused on developing realistic, terminal-based scientific and technical tasks for Terminal Bench Science. This role involves ensuring mathematical rigor, reproducibility, and challenge quality in tasks that span numerical and applied mathematics, scientific computing, optimization, statistics, modeling, computational algebra, and formal verification.

Key Responsibilities:
- Review and validate tasks comprehensively, 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 demand genuine multi-step reasoning rather than simple lookups or single library calls.
- Confirm appropriate use of exact, symbolic, arbitrary-precision, or floating-point computations.
- Assess that numerical tolerances align with the problem’s conditioning.
- Design and review graders based on mathematical properties such as residuals, feasibility, optimality certificates, invariants, error bounds, or proof checking.
- Guarantee reproducibility through pinned tools, libraries, solver versions, and dependencies.
- Detect and prevent hard-coded solutions, test-file leakage, and other bypass methods.
- Provide precise, actionable feedback and track trainer revisions to completion.
- Mentor and onboard trainers on mathematical rigor, task design, coding standards, and evaluation criteria.
- Allocate work, monitor quality and throughput, and escalate blockers as needed.
- Maintain pod documentation including guidelines, recurring issues, and exemplary tasks.
- Collaborate with the Mathematics Team Lead and other stakeholders to enhance benchmark quality.

Required Qualifications:
- Ph.D., postdoctoral experience, or equivalent advanced expertise in mathematics, applied mathematics, statistics, or a closely related discipline.
- Strong programming skills in Python, Julia, C/C++, MATLAB/Octave, or computer algebra systems.
- Proficiency with Linux and terminal environments.
- 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.
- Proven experience mentoring or leading small technical or research teams.
- Excellent written communication skills with the ability to provide clear, constructive feedback.
- Capability to assess reproducibility, test reliability, and scientific validity of computational tasks.

Preferred Qualifications and Benefits:
- Familiarity with libraries and tools such as NumPy, SciPy, SymPy, mpmath, SageMath, PARI/GP, GAP, Macaulay2, or Mathematica-like workflows.
- Experience with ODE/PDE frameworks like FEniCS, Firedrake, DifferentialEquations.jl, PETSc.
- Knowledge of optimization frameworks including CVXPY, JuMP, Pyomo, HiGHS.
- Exposure to proof assistants such as Lean/mathlib, Coq/Rocq, Isabelle.
- Experience with Docker, Git, continuous integration systems, and automated testing.
- Background in designing benchmarks, competition problems, or computational evaluations.
- Experience evaluating AI coding, reasoning, or terminal agents.
- Involvement in 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:
- Commitment of at least 4 hours per day, totaling a minimum of 40 hours per week, with a required 4-hour overlap with Pacific Standard Time (PST).
- Employment type is contractor assignment without medical or paid leave benefits.
- Contract duration is 4 weeks, with an expected start date as early as next week.