Design, develop, and maintain algorithms for engineering applications, manage datasets, and implement machine learning workflows in an AI Copilot startup.
We are an MIT-born, venture-backed Silicon Valley startup building a real-life 'Jarvis'—an AI Copilot for design and manufacturing. Our goal is to utilize advanced AI, physics simulation, and computer graphics to reduce costs and improve engineering productivity across all steps of the design and manufacturing process.
Responsibilities
- Design, develop, and maintain geometry processing and simulation algorithms for engineering applications.
- Build services for reading, processing, and writing 2D/3D engineering data.
- Develop rendering modules for generating 2D/3D visual assets.
- Curate and manage large-scale datasets for learning-based systems.
- Implement and optimize post-training workflows for machine learning models.
- Contribute to the development of domain-specific languages for engineering tasks.
What we are looking for
- 5+ years of academic or industry experience in one or more of the following areas: Geometric Processing, Simulation, Optimization, Machine Learning, or Domain-Specific Languages.
- BSc or MSc in Computer Science, Engineering, or a related field.
- Proficient in writing clean, modular, and maintainable Python code.
- Experience with dataset creation and data pipeline development.
Bonus Points
- PhD or MS with a focus in Computational Design, Simulation, or AI.
- Experience developing CAD/CAM/CAE software tools.
- Experience developing or fine-tuning large language models (LLMs), including post-training methods such as quantization, pruning, distillation, or reinforcement learning.
- Experience designing or implementing DSLs or compilers.
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