Job Requirements:

- Education &
- Expertise: Masters degree or PhD in Electrical, Mechanical, Aerospace, with 10+ years of hands-on engineering design experience.

- Simulation Tooling: Proficiency with at least one domain-relevant open-source simulation package (e.g., ngspice, PySpice, OpenFOAM, FEniCSx, CalculiX, python-control, CadQuery, build123d, OpenModelica, Cantera, Gmsh) combined with strong Python scripting skills.

- AI Evaluation &

- Failure Diagnostics: Hands-on experience with modern LLMs/coding agents and evaluation concepts (pass@k, failure-mode analysis, nondeterministic behavior), with the ability to audit trajectory logs and isolate core reasoning/tool-use failures.

- Domain Rigor &

- Precision: Uncompromising attention to physical plausibility, unit consistency, boundary conditions, convergence criteria, and technical documentation.

- Availability &

- Commitment: Talent must have weekend on-call availability (part-time engagement is acceptable).

- Technical Infrastructure: Personal desktop/laptop equipped with a stable, high-speed internet connection in a remote setup.

Job Responsibilities:





- Model-Breaking Problem Design: Author original, self-contained engineering design tasks with competing constraints, explicit optimization targets, validated reference solutions, and objective autograders.

- Setting &
- Simulation Integration: Build, run, and validate problem environments using open-source simulation tools and custom Python test benches.

- Trajectory Analysis &

- Failure Mode Taxonomy: Evaluate coding agent outputs and execution logs across repeated trials to identify systemic failure modes (e.g., misinterpreting simulator feedback, premature design convergence, physically impossible geometries).

- Difficulty Calibration &

- Benchmark Refinement: Iteratively refine problem difficulty based on empirical model performance data without introducing ambiguity or missing information.

- Cross-Functional Collaboration: Partner with AI researchers, pod leads, and domain experts to integrate high-rigor benchmarks into the model evaluation pipeline.

📌 Engineering Expert (Gurugram)
🏢 Crossing Hurdles
📍 Gurugram