Pod Lead - Chemistry (Terminal Bench Science) | $20 - $28/hr

Codefeast; India; A distancia; INR 2.619.000 - 3.667.000; A tiempo parcial

Ventajas ofrecidas por este puesto de trabajo

Remote work

Descripción de la vacante

Codefeast is seeking an expert in chemistry to lead a pod of trainers for Terminal Bench Science. You will review tasks for chemical correctness, reproducibility and safety, coaching trainers to deliver high-quality, multi-step problems.

You will guide task design, ensure proper validation of energies, geometries, and thermodynamics, and mentor junior staff. Start date is immediate; engagement length is 3 weeks with 4+ hours daily.

Formación

• Ph.D. or equivalent advanced experience in chemistry or related field.
• Strong programming skills in Python, C/C++, Julia or Fortran and Linux proficiency.
• Hands-on experience with computational chemistry, molecular simulation, cheminformatics, or chemical data analysis.
• Experience mentoring or leading small technical or research teams.
• Excellent written communication for precise feedback.

Responsabilidades

• Review trainer tasks end to end, including task statements, structures, spectra and datasets, force-field parameters, environments, reference solutions, and tests.
• Verify tasks reflect authentic chemistry research workflows and require multi-step reasoning, not single-lookups.
• Check software versions, force fields, basis sets, functionals, and dependencies for reproducibility.
• Validate chemical correctness: units (Hartree, eV, kcal/mol, kJ/mol), charge, spin, stereochemistry, method specs, SCF and geometry convergence.
• Ensure graders verify energies, geometries, thermodynamics, rate constants, spectra, or molecular properties rather than formatting.
• Screen tasks for chemical safety and dual-use concerns; escalate hazardous content.

Conocimientos

Python

C/C++

Julia

Fortran

Linux

Terminal

Educación

Ph.D.

Postdoctoral experience

Descripción del empleo

Pod Lead - Chemistry (Terminal Bench Science) | $20 - $28/hr

Qualification: Ph.D., postdoctoral experience, or equivalent advanced experience in chemistry or a closely related field.

Job Type: Contractor assignment

Location: Remote

Domain: Chemistry | Computational Science | AI Training

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.

Key Responsibilities

• 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.

Key Requirements

• 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.
• Start Date: Immediate
• Engagement Length: 3 weeks
• Commitment: At least 4 hours per day and minimum 40 hours per week, with an overlap of 4 hours with PST.