AI Engineer

About Us

• We're building a next-generation AI enabled assistant for hardware designers — one that doesn't just understand design, but helps improve it. Our system blends machine learning, 3D geometry, simulation, and constraint reasoning to guide engineers through meaningful design exploration
• We are building foundation models for geometry and physics. Our first model is shipped and we are expanding our capabilities!
• We are backed by Khosla Ventures and Eclipse Ventures

We’re looking for an AI engineer or applied researcher who can help us build intelligent systems that suggest design improvements
. This role is about understanding how a design could be better, and building models that can do that too.

You might reach for RL, graph-based approaches, gradient-based optimization, or surrogate modeling. What matters most is that you can pick the right tool, and you care about how well it integrates into the broader design process.

• 6+ Years experience applying ML or optimization methods to real-world design, modeling, or control problems.
• Solid understanding of reinforcement learning, structured search, or other agent-based approaches — but not ideological about them.
• Comfort working with 3D geometry, simulation APIs, or CAD tools in the loop.
• Strong software skills (e.g., Python, PyTorch, JAX) and a systems mindset.
• Build and ship critical product features
• Learn a lot while building products that engineers will love. Also learn about entrepreneurship!

• Experience building design space exploration tools or optimization pipelines for CAD, FEA, or mechanical systems.
• Understanding of constraint programming, multi-objective optimization, or design-for-manufacturing principles.
• Familiarity with agent architectures, hierarchical control, or physical embodiment.

• We’re not chasing toy benchmarks or leader board wins.
• You’ll be part of a team that cares deeply about real-world impact, clean abstractions, and usable AI tools for human designers.
• You’ll have autonomy to pursue principled approaches, backed by a strong foundation in AI and design engineering.