Spatial Computing Research Engineer

We are conquering the $400B Virtual Training and Simulation market by building 3D interactive applications that use next-generation neural rendering techniques and spatial reasoning AI. Backed by a16z Speedrun and Owl Ventures, we are actively fulfilling a government contract and are looking to quickly expand across many heavily regulated industries.

Core Responsibilities

• Convert research into shippable product: You will primarily be responsible for converting and integrating academic research code into robust engineering infrastructure that will support our products.
• Understand state of the art spatial computing research: Stay current with the latest spatial computing research relevant to our product. This may include, but is not limited to:
  • 3D Neural Rendering & Gaussian Splatting
  • Situated 3D Reasoning with Vision-Language Models
  • Dynamic 4D Capture Techniques
    
  • Systems for Large Area 3D Reconstruction
  • Neural Representations of Different Sensory Modalities (Electro-Optical, Radar, Sonar, SAR, etc.)
• Collaborate with Cross-Functional Members: Work closely with other members of the team and customers to create cohesive and engaging user experiences.
• Maintain Code Quality: Follow and contribute to our coding standards, participating in code reviews to maintain a high-quality codebase. Optimize code performance where necessary and ship at a high development velocity.

Requirements

• Bachelors and masters degrees in CS, EE, Physics, or a related discipline
• Strong analytical and reasoning skills with an emphasis on innovative and practical solutions
• Excellent programming skills with a preference for experience in Python and C++
• Strong familiarity in at least one (preferably many) of the following research domains:
  • Graphics (Neural Radiance Fields, Gaussian Splatting, Point Clouds/Voxels/Meshes)
  • Computer Vision (Object Detection, Segmentation, SLAM, 3D Reconstruction)
  • ML Systems (Transformers, Large Language Models, Large World Models)
• Ability to adapt a fast-changing startup environment, learn new technologies on the fly, and wear many hats