Job Description
This role involves developing and defining the perception architecture for Nuro's self-driving vehicles, focusing on creating foundational sensor data encoders that enable critical functionalities like object detection, mapping, and scene understanding using advanced machine learning techniques.
Key Responsibilities
- Define and develop the perception architecture for Nuro Driver.
- Develop training techniques for the foundational perception encoder.
- Optimize sensor data processing for object detection, tracking, and scene understanding.
- Apply machine learning expertise to balance model performance, latency, and maintenance.
- Contribute to research and development in multi-modal models and large-scale model training.
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 with demonstrated experience in both high-level and low-level programming languages, specifically Python and C.
- Experience communicating clearly on complex technical topics across a range of stakeholders and leadership.
- 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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