Research Engineer - 3D Vision and Generation, Self-Driving
Research Engineer focusing on 3D vision, Gaussian splatting, foundation models, and generative techniques for self-driving applications. Conducts cutting-edge research, publishes at top conferences, and deploys algorithms to production autonomy systems. Requires hands-on experience in 3D/ML for AV/robotics, Python/PyTorch proficiency.
Responsibilities
- Conduct research on 3D vision related topics including 3D foundation model, multi-modal pretraining, Gaussian splatting, world foundation model with applications to autonomous driving
- Work closely with Research Scientists and interns on high-quality research publications to submit to top-tier conferences
- Collaborate with our engineering teams on ADAS, data, and simulation to deploy end-to-end algorithms for mass production vehicles, and neural simulation/generation for tools supporting autonomy development
Requirements
- Hands-on experience in at least one of the following fields:
- 3D reconstruction with Gaussian splatting
- 3D / multi-modal foundation model and its pretraining
- World foundation model and video generation
- 3D/multi-view end-to-end models for autonomous driving or robotics
- Passion for next-generation, scalable autonomy and robotics for real-world systems
- Strong engineering and research skills and the ability to work both independently and collaboratively on projects
- Technical experience in: Python, PyTorch, computer vision, robotics systems, and distributed machine learning model training
Nice to Have
- Industry experience on relevant topics (self-driving application preferred)
- MSc or PhD in machine learning and computer vision with autonomy and robotics applications or closely related field
- Passion for building and shipping customer-focused software frameworks or tool
Compensation
Base salary range: $126,000 - $423,000 USD annually (full-time position). Total compensation includes equity, comprehensive health/dental/vision/life/disability insurance, 401k with employer match, learning/wellness stipends, and paid time off.
Machine Learning Platform Engineer
Build and operate the ML platform to productionize models, enable real-time inference, and manage the full ML lifecycle with MLOps best practices. Requires 3+ years platform engineering and 1+ years owning ML systems end-to-end.