Developing and implementing state-of-the-art state estimation and calibration algorithms for autonomous driving technology.
Requirements
- 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.
- Deep understanding of 3D geometry and state estimation fundamentals.
- Proficiency in systems coding.
- Experience in building offline/online state estimation and/or calibration algorithms with camera, lidar, radar, IMU, etc.
- Experience in simulating/modeling real sensors (camera, lidar, radar, IMU, etc...), including noise modeling.
Responsibilities
- Research and develop state-of-the-art state estimation and calibration algorithms combining classic robotics and modern ML techniques.
- Analyze and characterize the accuracy and performance of state estimation and calibration algorithms.
- Integrate state estimation and calibration pipelines into the autonomy system and analyze onboard performance and resource utilization.
- Work cross-functionally with other autonomy teams to accelerate the training of ML models and end-to-end performance evaluation.
- Answer critical questions about sensor data and autonomy performance.
Other
- One of: 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.
- Travel requirements not mentioned
- Clearance requirements not mentioned
- Visa requirements not mentioned
- Soft skills not mentioned
- Base pay range between $167,200 and $250,800 for the level at which this job has been scoped.
