Senior/Staff Machine Learning Engineer, Sensor Simulation
Develop synthetic sensor simulation models and algorithms using ML techniques like NeRF and Gaussian splatting to generate photorealistic images and realistic lidar/radar data for autonomous vehicles. Requires advanced degree plus 3-5+ years experience, strong ML fundamentals, and Python/deep learning expertise.
About the job
Responsibilities
- Research, develop, and implement state-of-the-art synthetic sensor simulation methods
- Analyze and characterize the realism and utility of synthetic sensor data
- Answer critical questions about sensor data and autonomy performance
- Collaborate with stakeholders across autonomy, infrastructure, and systems teams on map needs and requirements
Requirements
- One of the following:
- PhD in machine learning, computer science, electrical engineering, robotics, or related field, and 3+ years of industry experience
- Masters and 4+ years of industry experience
- 5+ years of industry experience
- Deep understanding of ML fundamentals with hands-on experience in training and evaluating modern ML models
- Strong Python skills with experience in deep learning frameworks, e.g., PyTorch, TensorFlow, or Jax
Nice-to-Haves
- Deep understanding of 3D geometry and state estimation fundamentals
- Proficiency in systems coding
- Experience in simulating/modeling real sensors (camera, lidar, radar, IMU, etc), including noise modeling
- Experience in modern ML graphics techniques, e.g., NeRF, Gaussian Splatting, and/or generative models
- Experience in building ML pipelines and optimizing/productizing ML models
- Demonstrated research publications in top conferences (e.g. NeurIPS, ICLR, ICML, CVPR, RSS, CoRL, ICRA)
Compensation
- Base pay range: $193930 - $291150 (depends on experience, qualifications, education, location, and skills)
- Eligible for annual performance bonus, equity, and competitive benefits package
Skills
Machine Learning, Python, PyTorch, TensorFlow, JAX, Nerf, Gaussian Splatting, 3D Geometry, Sensor Simulation, Lidar, Radar, Generative Models
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