We are looking for a MLOPS simulation engineer who can help move the autonomy simulation platform onto NVIDIA Omniverse. The pod will stabilize the current platform, migrate it from its existing engine (CARLA) to Omniverse and Isaac Sim, and expand the scenario framework that autonomy teams use to test their software at scale. This role owns the data side of the migration: connecting the client's existing simulation data to Isaac Sim and building the pipelines and services that feed the platform.
Essential functions
- Build synthetic data pipelines with Replicator for the client's perception and autonomy models.
- Design domain randomization strategies and measure their effect on model performance.
- Mix synthetic and real data and track what improves training.
- Build agents that generate, label and package synthetic datasets at scale.
Qualifications
- Synthetic data generation with NVIDIA Omniverse Replicator.
- Domain randomization: lighting, materials, poses, weather, sensor parameters.
- Perception workflows in PyTorch: training and evaluating models on synthetic and mixed real/synthetic data.
- Annotation output from simulation (boxes, segmentation, depth) in formats training pipelines use.
- Has built simulation AI agents or automation for data generation
- Strong Python programming skills
- Bachelor's or Master's degree in Computer Science, Engineering, or a relevant technical discipline.
Would be a plus
- Closing the sim-to-real domain gap for perception models.
- Synthetic data at scale on GPU clusters.
- Experience with real sensor data (camera, LiDAR) from vehicles or machines.
We offer
- Opportunity to work on cutting-edge projects
- Work with a highly motivated and dedicated team
- Competitive salary
- Flexible schedule
- Benefits package - medical insurance, vision, dental, etc.
- Corporate social events
- Professional development opportunities
- Well-equipped office
Please note that all onboardings must occur in person and you may be asked to travel to attend. 
