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Pod Lead — Material Sciences (Terminal Bench Science)
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About the Role
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. We are seeking an experienced Materials Science expert to lead a team of technical trainers developing realistic, terminal-based scientific tasks for a frontier AI training and evaluation initiative.
What You'll Do
- Lead and mentor a pod of technical trainers, ensuring consistent quality, productivity, and timely delivery of materials science tasks.
- Review scientific tasks end to end, including problem statements, crystal structures, interatomic potentials, thermodynamic databases, simulation inputs, reference solutions, and automated tests.
- Validate tasks involving density functional theory (DFT), molecular dynamics, computational thermodynamics, phase diagrams, crystallography, materials characterization, mechanical properties, semiconductors, and energy materials.
- Ensure tasks reflect realistic materials research workflows and require meaningful multi-step scientific reasoning rather than simple database lookups or library calls.
- Verify scientific correctness across units, crystal symmetry, convergence criteria, electronic structure calculations, thermodynamic consistency, and simulation parameters.
- Validate computational environments, scientific software, pseudopotentials, interatomic potentials, and dependencies to ensure reproducible results.
- Review automated graders to ensure they evaluate meaningful scientific outputs such as lattice parameters, formation energies, band gaps, elastic constants, phonon properties, phase fractions, diffusion coefficients, and microstructure metrics.
- Identify technical inaccuracies, unrealistic assumptions, incorrect numerical tolerances, and opportunities to bypass scientific calculations or simulations.
You're a Good Fit If You
- Required skills: Basic Programming
- Ph.D., postdoctoral experience, or equivalent advanced technical experience in Materials Science, Metallurgy, or a closely related discipline.
- Strong programming skills in Python, C/C++, Fortran, or Julia, with proficiency in Linux and terminal-based environments.
- Hands-on expertise in at least one major area: atomistic simulation, computational thermodynamics, mesoscale modeling, electronic structure calculations, or materials characterization data analysis.
- Strong understanding of materials science fundamentals, numerical methods, computational modeling, and scientific validation.
- Experience reviewing complex technical work, scientific code, computational simulations, manuscripts, or research outputs.
- Ability to evaluate scientific assumptions, numerical accuracy, simulation convergence, and the reliability of computational results.
- Strong analytical judgment with the ability to identify technical errors, edge cases, and flawed scientific assumptions.
Role Highlights
Pay & Payout
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Common Questions
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