Sensor Sim - ML Engineer
Develops and deploys generative ML techniques for production-grade sensor simulation (Lidar, Radar, Cameras) in autonomous systems. Collaborates with research, rendering, and physics teams; requires 5+ years ML experience, Bachelor's in CS, and expertise in large models and 3D geometry.
About the job
Responsibilities
- Drive research, development and deployment of generative and other machine learning techniques into our sensor simulator.
- Work closely with rendering and physics-based modeling teams to build novel approaches fusing the best of all techniques.
- Focus on projects with a clear path to production value and customer impact.
Requirements
- Bachelor's degree in Computer Science, Software Engineering, or equivalent
- 5+ years of experience building software components or (sub)systems that address real-world machine learning challenges
- Passion for turning domain expertise into tooling that boosts the productivity of teams working on various real-world applications of autonomous systems
- Hands-on experience with evaluation and optimization for large generative models
- Hands-on experience with agentic system design
- Deep understanding of machine learning foundations who can apply various techniques to new problems
- Understanding of 3D geometry, optical flow or video generation
Nice to Have
- Experience working with Generative World Models (Cosmos, UniSim, sora-style architectures)
- Experience with robotics simulation products (IssacSim, MuJoCo, Omniverse, USD)
- Experience with applying synthetic data to machine learning tasks
- Hands on experience with characterization of models for Lidar, Radar, and Camera
Compensation
- Base salary range: $125,000 - $222,000 USD annually
- Equity, comprehensive health, dental, vision, life and disability insurance, 401k with employer match, learning and wellness stipends, paid time off
Skills
Machine Learning, Generative Models, Sensor Simulation, Lidar, Radar, Camera, 3D Geometry, Optical Flow, Video Generation, Agentic Systems, Robotics Simulation, Synthetic Data, PyTorch, TensorFlow
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