Job Description
The role involves building and optimizing core machine learning infrastructure for autonomous driving systems at Nuro, including model training pipelines and deployment of optimized models on self-driving robots. Candidates will collaborate with various teams to enhance the performance and safety of autonomous technologies.
Key Responsibilities
- Optimize Nuro's autonomy stack using optimization techniques like quantization, distillation, and model compression.
- Collaborate with autonomy engineers to optimize, validate, and deploy large language models.
- Develop and maintain a model compiler framework, FTL.
- Write robust, high-quality software to enhance vehicle navigation safety.
- Design and implement end-to-end learned ML solutions in collaboration with machine learning domain experts.
Requirements
- 3 years of relevant experience in ML optimization infrastructure.
- Experience with ML optimization techniques such as quantization and pruning, and ML compilers.
- Experience maintaining, profiling, and optimizing GPU ML compilers runtimes.
- Proficient in Python and working experience with C and CUDA.
- Working experience with deep learning frameworks like PyTorch, Jax, Tensorflow, Keras.
Benefits & Perks
Compensation/salary range: 167,200 to 303,050
Annual performance bonus
Equity
Competitive benefits package
Ready to Apply?
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