Develop algorithms for geometric understanding, constraint solving and multi-objective optimization, including evolutionary methods where appropriate.
Build structured representations and reliable tools that enable AI systems to work with CAD and engineering data.
Design extensible systems that combine geometric algorithms, engineering rules and learned approaches.
Own problems from experimentation through evaluation and production integration.
Turn expert feedback into evaluations and, where permitted, training data. Explore fine-tuning, preference learning and reinforcement learning where they measurably improve results.
Improve correctness, performance and maintainability across the systems you build.
Strong Python skills and software engineering fundamentals; comfortable working in C++ when needed.
Evidence of exceptional engineering or research work, with the ability to explain your decisions and tradeoffs.
Comfortable with mathematical problems involving geometry, linear algebra or optimization.
Able to turn loosely defined problems into practical implementations and meaningful evaluations.
Effective with coding agents, while understanding and verifying the code you ship.
Curious about mechanical engineering and how machines represent and reason about physical objects.
Experience with CAD kernels, geometric algorithms, multi-objective or evolutionary optimization, constraint solvers, spatial reasoning, applied ML or agentic systems is a strong plus. You don’t need experience in every area.
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