Job Description
This role involves developing and optimizing the perception architecture for Nuro's self-driving vehicles, focusing on processing sensor data to enable critical functionalities like object detection, mapping, and scene understanding using advanced machine learning techniques.
Key Responsibilities
- Define the perception architecture of Nuro Driver.
- Develop training techniques for the perception foundation encoder.
- Design and optimize the encoder to process sensor data into unified feature representations.
- Contribute to functionalities such as object detection, tracking, online mapping, and scene understanding.
- Apply machine learning expertise to balance model performance, latency, and maintenance complexity.
Requirements
- Ph.D. level research experience in areas such as multi-modal models, large multi-task vision models, large scale model training, and model distillation.
- At least 3 years of experience working deeply on a machine learning project with material contributions.
- Strong software engineering fundamentals and demonstrated experience in both high-level and low-level programming languages, specifically Python and C.
- Publication record at major conferences such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, CoRL, RSS, or ICRA.
Benefits & Perks
Compensation/salary range: $193,930.00 to $291,150.00 per year
Work schedule: Not specified
Work environment perks: Not specified
Additional benefits: Annual performance bonus, equity, competitive benefits package
Ready to Apply?
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