Pod Lead — Chemistry(Terminal Bench Science)

Review and ensure chemical accuracy in scientific task designs for training.

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 Chemistry 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 chemical correctness, reproducibility, safety, 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, molecular structures, spectra and datasets, force-field parameters, environments, reference solutions, and automated tests.
• Verify that tasks reflect authentic chemistry research workflows and require genuine multi-step reasoning rather than a single library call or lookup.
• Check that software versions, force fields, basis sets, functionals, and dependencies are pinned and that results are reproducible.
• Validate chemical correctness, including units such as Hartree, eV, kcal/mol, and kJ/mol; charge and spin multiplicity; stereochemistry and tautomer handling; method specifications; SCF and geometry convergence; frequency checks for minima and transition states; equilibration; and sampling adequacy.
• Ensure tolerances reflect method-dependent, numerical, and stochastic variation without accepting chemically incorrect results.
• Ensure graders verify energies, geometries, thermodynamic quantities, rate constants, spectral assignments, or molecular properties rather than formatting.
• Ensure tasks cannot be gamed through hard-coded outputs, reading test files, or bypassing the intended computation.
• Screen tasks for chemical safety and dual-use concerns.
• Escalate content involving the synthesis or enhancement of hazardous, toxic, or controlled substances.
• Provide clear, actionable written feedback and track revisions through closure.
• Onboard and mentor trainers on task design standards, common pitfalls, and grader design.
• Allocate work across the pod and track throughput and quality metrics.
• 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 chemistry or a closely related field.
• Strong programming skills in Python, C/C++, Julia, or Fortran, with Linux and terminal proficiency.
• Hands-on experience with computational chemistry, molecular simulation, cheminformatics, or chemical data analysis.
• Proven experience reviewing code, analyses, manuscripts, or research outputs.
• Experience mentoring or leading small technical or research teams.
• Excellent written communication skills for providing precise, constructive feedback

Nice to have:

• Familiarity with PySCF, Psi4, ORCA, xTB, CP2K, NWChem, GROMACS, OpenMM, AmberTools, RDKit, Open Babel, ASE, or MDAnalysis.
• Experience with free-energy methods, reaction mechanism analysis, machine-learned potentials, or spectroscopy simulation.
• Familiarity with Docker, Git, CI systems, automated testing, and HPC environments.
• Experience designing benchmarks, programming tasks, or simulation-based evaluations.

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]

Skills: Basic Programming, Academic Research