Get your free practice interview for this role
Turing screens applicants online, often with an AI interview. micro1 offers a free, 18-minute AI practice interview with feedback, and we picked the one closest to this role: Data Annotator. It covers:
Here’s your practice interview
Allow your microphone when it asks, find a quiet spot, and give yourself about 20 minutes. We’ve also emailed you the link and the free ebook.
Step 2: when you feel ready, apply.
The practice interview is free and run by micro1. Land Remote Jobs is an independent job board, not part of micro1, Mercor or Turing. Practising helps you prepare; it can’t guarantee the result of your real interview. Want more tips? Read our guide to acing the remote job interview.
Apply for this role
You apply on Turing's own site. It’s free, and you can apply even if you skip the practice.
Who this role suits
Researchers and PhD holders who want to use their subject expertise on remote, flexible projects.
Full job description
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]
Last checked open on Oct 28, 2026. Job description provided by Turing.
Something not working? Tell us
If the practice interview or the apply link doesn’t open, or the job looks closed, let us know and we’ll fix it.
Thanks, we got it. We’ll check this job’s links and reply by email if you left one.