5+ years of academic or industry experience in 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
Requirements:
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
Job description
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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
