About The Position

The company is building an AI assistant for hardware designers, with a mission to help hardware designers and engineers iterate through designs much faster using geometry- and physics-driven foundation models. The role will help improve the company’s MVP by developing the pipelines and tools that support the product, accelerate development from coding through deployment, and orchestrate data flows throughout the deployed product. The engineer will develop product features to improve scalability and APIs for complex engineering workflows, integrate LLM or VLM infrastructure, and establish an MLOps framework for training deep learning architectures on geometry and physics data. The role also contributes to product strategy and roadmap planning with early customers and design partners, and builds and ships critical product features. The position offers opportunities to learn about product building and entrepreneurship.

Requirements

  • At least 6 years of experience developing and shipping features in high-performance computing.
  • Proficiency in C++, Python, or another language needed to set up a system.
  • Experience with tools such as gRPC, Protocol Buffers, Docker, Kubernetes, and Bazel or another language-agnostic build system.

Nice To Haves

  • Proficiency using cloud compute for data generation, scraping, and enabling data science teams to train models with MLOps.
  • CUDA experience (not required).
  • Frontend experience.
  • Startup experience.

Responsibilities

  • Develop key product features, including improving scalability and APIs for more complex engineering workflows.
  • Build pipelines and tools that support the product and accelerate development from development to deployment.
  • Orchestrate data flows throughout the deployed product.
  • Set up and integrate LLM or VLM infrastructure.
  • Set up an MLOps framework for training deep learning architectures for geometry and physics data.
  • Assist with product strategy, roadmap planning, and prioritization in partnership with early customers and design partners.
  • Build and ship critical product features.
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