Kerja Sepenuh Masa, Pod Lead – Mechanical - Aerospace Engineering (Terminal Bench Science) di ETeam - Maukerja

Hi, I hope you’re doing well.

My name is Manas, and I’m a recruiter with eTeam. I’m reaching out regarding an urgent Pod Lead – Mechanical & Aerospace Engineering opportunity with Turing, a 4-week remote contract role.

This opportunity is ideal for advanced Mechanical or Aerospace Engineering professionals with strong programming, engineering simulation, technical validation, and team leadership experience.

1. Role Overview – Quick Snapshot

Company: Turing

Position: Pod Lead – Mechanical & Aerospace Engineering (Terminal Bench Science)

Location: Remote – Malaysia

Experience: Ph.D., postdoctoral experience, or equivalent advanced technical experience in Mechanical Engineering, Aerospace Engineering, or a closely related discipline

Engagement: Short-Term Contract – 4 weeks

Start Date: Immediate / Expected to start next week

Working Schedule: Minimum 40 hours per week, with at least 4 hours of commitment per day

Working Hours: 8 hours per day, with a minimum 4-hour overlap with Pacific Standard Time (PST)

Team Size: Approximately 5–10 technical trainers

Work Mode: Fully Remote

Employment Arrangement: Contractor assignment; no medical or paid leave

2. Job Description

About Turing

Based in San Francisco, California, Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises deploying advanced AI systems.

Turing accelerates frontier research through high-quality data, advanced training pipelines, and AI researchers specializing in coding, reasoning, STEM, multilinguality, multimodality, and agents. It also helps enterprises transform AI from proof of concept into proprietary intelligence with reliable systems that deliver measurable business impact.

Role Summary

Lead a pod of approximately 5–10 technical trainers responsible for developing and validating realistic, terminal-based Mechanical and Aerospace Engineering tasks for a frontier AI training and evaluation initiative.

The role involves reviewing engineering tasks for technical accuracy, reproducibility, numerical reliability, and evaluation quality. You will mentor trainers, maintain technical quality standards, validate simulation workflows, and ensure consistent and timely delivery.

Key Responsibilities

Lead and mentor a pod of approximately 5–10 technical trainers, ensuring consistent quality, productivity, and timely delivery of engineering tasks.

Review engineering tasks end-to-end, including problem statements, geometry and mesh files, simulation inputs, material properties, reference solutions, and automated tests.

Validate tasks involving finite-element analysis (FEA), computational fluid dynamics (CFD), thermodynamics, heat transfer, dynamics, robotics, flight simulation, propulsion, and orbital mechanics.

Ensure engineering tasks reflect realistic Mechanical and Aerospace Engineering workflows and require meaningful multi-step technical reasoning.

Verify engineering correctness across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability.

Validate computational environments, simulation tools, solvers, and dependencies to ensure reproducible results.

Review automated graders to ensure they evaluate meaningful engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins.

Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and opportunities to bypass engineering calculations or simulations.

Provide clear, actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval.

Onboard trainers, allocate work, monitor quality and throughput, escalate blockers, and maintain technical documentation and best practices.

Required Qualifications

Ph.D., postdoctoral experience, or equivalent advanced technical experience in Mechanical Engineering, Aerospace Engineering, or a closely related discipline.

Strong programming skills in Python, C/C++, Fortran, Julia, or MATLAB/Octave.

Proficiency in Linux environments.

Hands-on expertise in at least one major engineering domain: FEA, CFD, dynamics, flight simulation, thermal modeling, astrodynamics, guidance, navigation and control (GNC), or propulsion modeling.

Strong understanding of engineering simulation, numerical methods, computational modeling, and technical validation.

Experience reviewing complex technical work, engineering simulations, computational models, or research outputs.

Ability to evaluate engineering assumptions, numerical accuracy, solver convergence, and computational reliability.

Strong analytical judgment and the ability to identify technical errors, edge cases, and flawed engineering assumptions.

Experience mentoring, reviewing, or leading small technical teams.

Excellent written communication skills for providing precise technical feedback and documenting quality standards.

Nice-to-Have Skills

Experience with engineering simulation tools such as OpenFOAM, SU2, CalculiX, Code_Aster, FEniCS, Elmer, Gmsh, FreeCAD, CadQuery, MuJoCo, ROS, XFOIL, AVL, OpenVSP, JSBSim, OpenMDAO, pyCycle, poliastro, Orekit, GMAT, or SPICE.

Familiarity with commercial engineering software such as ANSYS, Abaqus, COMSOL, or NASTRAN, including reproducing workflows using open-source tools.

Experience with state estimation, trajectory optimization, topology optimization, aeroelastic analysis, or multidisciplinary design optimization.

Familiarity with Docker, Git, CI/CD pipelines, and automated testing.

Experience developing or evaluating AI coding agents, terminal-based agents, or LLM-generated engineering solutions.

Industry or agency experience in automotive, energy, manufacturing, robotics, aircraft, launch vehicles, satellites, or UAVs.

Prior experience in AI training, technical quality control, benchmark development, or evaluation programs.

Interested candidates may share their updated CV/Resume or connect with me directly:

• Direct Calls (Malaysia): +60 ************* 6540
• WhatsApp: +*************
• Email: *************