Mechanical & Aerospace Engineer Lead

• *Mechanical \& Aerospace Engineer Lead (AI Training \& Evaluation)**

Job Overview

We are seeking an experienced Mechanical or Aerospace Engineering expert to lead a team of technical trainers working on a frontier AI training and evaluation initiative.

As Pod Lead, you will supervise a team of approximately 5–10 technical trainers responsible for developing realistic, terminal\-based engineering tasks used to train and evaluate advanced AI models. You will ensure technical accuracy, reproducibility, engineering validity, and high\-quality evaluation standards across all deliverables.

This role is ideal for an engineering professional with advanced technical expertise, strong programming skills, and experience in engineering simulations, computational modeling, and technical team leadership.

Key Responsibilities

• Lead, mentor, and coordinate a team of 5–10 technical trainers to ensure consistent quality, productivity, and timely delivery.
• 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 tasks represent realistic engineering workflows and require meaningful, multi\-step technical reasoning.
• Verify engineering accuracy across units, equilibrium, conservation laws, boundary conditions, mesh convergence, solver tolerances, reference frames, and numerical stability.
• Validate computational environments, simulation tools, solvers, and software dependencies to ensure reproducible results.
• Review automated grading systems to confirm that they accurately evaluate engineering outputs, including stresses, deflections, natural frequencies, aerodynamic coefficients, thermal performance, orbital parameters, and safety margins.
• Identify technical inaccuracies, unrealistic assumptions, incorrect tolerances, and potential shortcuts that bypass meaningful engineering calculations or simulations.
• Provide clear, actionable technical feedback and ensure identified quality issues are resolved before task approval.
• Onboard trainers, allocate assignments, monitor quality and throughput, resolve or escalate blockers, and maintain technical documentation and best practices.

Required Qualifications and Skills

• 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 and command\-line workflows.
• Hands\-on expertise in at least one of the following areas:
• Finite\-Element Analysis (FEA)
• Computational Fluid Dynamics (CFD)
• Engineering dynamics and flight simulation
• Thermal modeling and heat transfer
• Astrodynamics and orbital mechanics
• Guidance, Navigation and Control (GNC)
• Propulsion modeling
• Strong understanding of engineering simulations, numerical methods, computational modeling, and technical validation.
• Experience reviewing complex technical work, engineering simulations, computational models, or research outputs.
• Ability to assess engineering assumptions, numerical accuracy, solver convergence, and computational reliability.
• Strong analytical and problem\-solving skills, with the ability to identify technical errors, edge cases, and flawed assumptions.
• Previous experience mentoring, reviewing, or leading small technical teams.
• Excellent written communication skills and the ability to document technical findings and provide precise feedback.

Preferred Qualifications

• 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 the ability to reproduce workflows using open\-source alternatives.
• Experience in state estimation, trajectory optimization, topology optimization, aeroelastic analysis, or multidisciplinary design optimization.
• Familiarity with Docker, Git, CI/CD pipelines, and automated testing frameworks.
• Experience developing or evaluating AI coding agents, terminal\-based agents, or AI\-generated engineering solutions.
• Industry or research experience in automotive, energy, manufacturing, robotics, aviation, launch vehicles, satellites, or UAVs.
• Previous experience in AI training, technical quality assurance, benchmark development, or model evaluation programs.

Engagement Details

• **Duration:** 4 weeks
• **Monthly Compensation:** ₹2\.19 lakh
• **Daily Commitment:** 8 hours
• **Time Zone Requirement:** Minimum 4 hours of overlap with PST
• **Role Type:** Short\-term contract

Pay: ₹219,000\.00 per month

Benefits

• Work from home

Application Question(s)

• What is your specialization in PHD?
• What is your total years of experience?

Education

• Doctorate (Preferred)

Work Location: Remote