Remote Physics Pod Lead - AI Task Quality & Mentoring

Turing Enterprises, Inc.; Fatih; Remoto; TRY 4.988.000 - 6.983.000; Part-time

Descrizione del lavoro

Turing Enterprises, Inc. is seeking an experienced Physics expert to lead a pod of trainers building realistic, terminal-based scientific tasks. You will review every task for physical correctness, reproducibility, and grader reliability, and coach trainers to deliver high-quality, challenging tasks.

You will onboard and mentor trainers, allocate work, track quality and throughput, and maintain pod documentation to ensure consistent standards across tasks and evaluations.

Competenze

• PhD or equivalent advanced physics experience.
• Strong programming in Python/C/C++, Julia or Fortran with Linux proficiency.
• Hands-on experience in computational physics, simulation, or physics data analysis.
• Proven track record reviewing code, analyses, or research outputs.
• Experience mentoring or leading small technical or research teams.

Mansioni

• Review trainer tasks end to end including statements, datasets, simulations, environments, reference solutions and tests.
• Verify tasks reflect authentic physics workflows requiring multi-step reasoning.
• Check tool dependencies are pinned and results are reproducible.
• Validate dimensional consistency, units, conservation laws, symmetries and numerical stability.
• Ensure graders verify observables or invariants rather than formatting, and prevent hard-coded outputs.

Conoscenze

Python

C/C++

Julia

Fortran

Linux

Mentoring

Formazione

Ph.D., postdoctoral experience, or equivalent advanced experience in physics

Strumenti

QuTiP

Qiskit

Kwant

ITensor

ROOT

Geant4

Astropy

Dedalus

MEEP

Descrizione del lavoro

Turing Enterprises, Inc. is seeking an experienced Physics expert to lead a pod of trainers building realistic, terminal-based scientific tasks. You will review every task for physical correctness, reproducibility, and grader reliability, and coach trainers to deliver high-quality, challenging tasks.

You will onboard and mentor trainers, allocate work, track quality and throughput, and maintain pod documentation to ensure consistent standards across tasks and evaluations.