Mechanical and Aerospace Engineering Task Lead – AI Project

🔥 14 hours ago

🌐 Pakistan, Indonesia, +4 more countries – Remote

🇵🇰 Pakistan – Remote 🇮🇩 Indonesia – Remote 🇰🇪 Kenya – Remote 🇹🇷 Turkey – Remote 🇳🇬 Nigeria – Remote 🇻🇳 Vietnam – Remote

⏳ Contract/Temporary

🟠 Senior

🤖 AI Engineer

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Gramian Consulting

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

Gramian Consulting is a remote-first consulting firm that connects engineering and data/AI talent with organizations through talent augmentation, recruiting, dedicated teams, and contractor management. The firm provides Data & AI services including LLM training and fine-tuning, AI agents and assistants, MLOps, and AI infrastructure, and it offers mentorship and education programs for career readiness, interview preparation, and international market orientation. Rooted in hands-on engineering and recruiting experience, Gramian helps clients scale technical teams and extract business value from AI while developing individual talent.

📋 Description

• Lead and mentor a team of 5–10 technical trainers, ensuring consistent task 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 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 assess 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 genuine engineering calculations or simulations. • Provide actionable technical feedback, track revisions, and ensure quality issues are resolved before task approval. • Onboard trainers, allocate work, monitor quality and throughput, resolve technical blockers, and maintain technical documentation and best practices. • Work as a senior/technical lead on advanced AI training and evaluation tasks for Gramian Consultancy’s engineering talent solutions.

🎯 Requirements

• PhD, postdoctoral experience, or equivalent advanced technical expertise 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 and command-line environments. • Hands-on expertise in at least one major area, such as 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 assess 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 precise technical feedback and documentation. • Minimum capacity of 40 hours per week. • Strong written English.