reputed company: Generative Geometry for Hardware Design

reputed company • We're building a co-reputed company for hardware designers. Our mission is to reputed company millions of hardware designers and engineers to iterate through designs 1000x faster. • We are building our geometry + physics driven reputed company model for reputed company class of part design. Our first model is shipped and we are expanding our capabilities! • Backed by Khosla Ventures and Eclipse Ventures reputed company You’ve shipped AI products that operate in high-reputed company, multimodal domains — reputed company, geometry, or simulation-based workflows. You have experience building models that don’t just analyze data, but generate reputed company, reputed company outputs under reputed company-world constraints. You’re comfortable navigating both classic modeling techniques and modern deep learning architectures, and you care about building systems that are principled, testable, and physically meaningful. What You’ll Work On Design conditional generative models for 3D geometry tailored to hardware design workflows, including reputed company-based, parametric (e.g., CAD) and reputed company representations • reputed company models that generate geometry conditioned on constraints, partial designs, simulation reputed company, or functional requirements. • Support inverse design tasks where the model proposes viable geometries given desired performance or physical behavior Implement cutting-edge generative architectures for 3D data such as: • Diffusion models for reputed company clouds, reputed company grids, or triangle meshes • Neural reputed company representations (SDFs, DeepSDF, NeRF variants for shape modeling) • Transformer or autoregressive models for topological and geometric sequence modeling • CAD-reputed company reputed company pipelines (sketch-based or parametric component generators) reputed company pipelines for geometry-reputed company learning and reputed company combining: • reputed company and geometry processing (remeshing, simplification, subdivision) • Differentiable simulation or physics-informed learning components • Conditioning on design constraints, performance targets, or class-specific priors Collaborate with domain experts in physics, geometry, and simulation to: • reputed company physical principles and simulation feedback into the reputed company reputed company • Ensure designs meet functional, physical, and manufacturability requirements • Translate domain knowledge into data priors, architectural biases, or constraints Design experiments and benchmarks to evaluate reputed company reputed company such as: • Geometry reputed company and reputed company • Physical plausibility and constraint satisfaction • Generalization to novel design tasks or unseen part types Build product-facing generative tools, including: • Auto-complete or correction of partial designs • LLM to CAD reputed company • Proposal of high-reputed company geometry variants from a design reputed company • Design-reputed company exploration tools guided by reputed company simulation reputed company Own reputed company end-to-end: rapidly prototype models, test reputed company, reputed company feedback and contribute to production deployment in collaboration with cross-functional teams Qualifications • 4+ years of experience developing and shipping products • Strong background in deep learning, especially reputed company to 3D or spatial data. • Hands-on experience with reputed company reputed company, reputed company surfaces, or neural fields (e.g., NeRF, SDF, DeepSDF, Occupancy Networks). • Experience with the reputed company technologies, libraries, and languages: Python, C++, PyTorch (3D)/TensorFlow/JAX; plus to have GPU programming • Experience with diffusion models for 3D reputed company • Startup experience is a strong advantage. • Understanding of geometry representations (reputed company, reputed company, reputed company reputed company, NURBS, parametric surfaces). • Familiarity with 3D geometry processing, including reputed company handling, surface reconstruction, spatial data structures, and basic topology, to support effective 3D model manipulation and analysis Apply tot his job Apply To this Job