Senior / Staff Research Engineer, Simulation Assets & Content Systems

Waabi Waabi · Robotics · Toronto, ON +3 · Remote · Autonomy & Algorithms

This role focuses on building and owning the end-to-end asset pipelines for a multi-sensor simulation stack in the autonomous transportation domain. It involves designing schemas, formats, and storage for a heterogeneous asset library, building tooling for inspection and curation, integrating cutting-edge research from neural rendering and generative AI, and collaborating with autonomy and safety teams to ensure the asset catalog meets training and evaluation demands. The role requires strong software engineering fundamentals, experience with 3D content pipelines, modern 3D representations, and cloud infrastructure.

What you'd actually do

  1. Architect and own asset pipelines end-to-end: From raw sensor logs all the way into simulation-ready representations (e.g., 3DGS, NeRF, mesh, hybrid), validation, packaging, and serving into Waabi World.
  2. Design schemas, formats, and storage for a heterogeneous asset library spanning traditional mesh/material assets, neural representations, and generative-model outputs. Ownership of design decisions ranging from formats and compression, to streaming, and cross-renderer interop.
  3. Build tooling and visualization that lets research scientists, simulation engineers, and technical artists inspect, compare, debug, and curate assets at the scale of tens of thousands of items — including search, similarity, lineage, and regression review.
  4. Integrate cutting-edge research into the pipeline — collaborate with the neural rendering and generative AI teams to productionize the latest reconstruction, diffusion, and world-model techniques as first-class steps in the asset lifecycle.
  5. Collaborate with autonomy and safety teams to ensure the asset catalog meets the diversity, realism, and coverage demands of training and closed-loop evaluation.

Skills

Required

  • Python
  • C++ or Rust
  • 3D content pipelines
  • modern 3D representations (NeRF, 3DGS, USD, mesh)
  • Cloud infrastructure (AWS, GCP)
  • GPU job orchestration
  • production-quality software development

Nice to have

  • NeRF
  • 3D Gaussian Splatting
  • OpenUSD
  • mesh/material/PBR
  • generative content

What the JD emphasized

  • Shipping Production Software
  • 3D Content Pipelines
  • modern 3D representations
  • Cloud Infrastructure at Scale

Other signals

  • building the content backbone of a best-in-class multi-sensor simulation stack
  • architect and own asset pipelines end-to-end
  • integrate cutting-edge research into the pipeline
  • collaborate with autonomy and safety teams to ensure the asset catalog meets the diversity, realism, and coverage demands of training and closed-loop evaluation