Software Engineer, ML Infrastructure, Optimization
$160.36k - $240.54kFull-time
Nuro
Who We Are Nuro believes self-driving vehicles are the most immediate and profound opportunity for AI to drive positive change in the physical world. Safer streets, more time for what matters, and easier access to the world around us, that’s why we’re building a universal autonomy platform: self-driving for all roads and all rides. Founded in 2016, Nuro is a physical AI company developing Level 4 autonomous driving technology for a wide range of vehicles, use cases, and markets. Powered by the Nuro Driver™, our universal autonomy platform enables the global mobility ecosystem to deploy autonomy at scale, from robotaxis and logistics fleets to personal vehicles. With years of real-world deployment experience and a flexible, partner-led business model, Nuro is working toward a future where millions of autonomous vehicles powered by our technology help make everyday life safer, easier, and more connected. Nuro has raised over $2B in capital from Uber, NVIDIA, Google, Softbank, Fidelity, T. Rowe Price, and other leading investors. About The Role The Autonomy ML Infrastructure team is responsible for building & improving the core infrastructure for autonomy teams at Nuro. In this role, you will work closely with teams across Nuro, to design, build and deploy core infrastructure components in machine learning model life cycle, to push the autonomous future forward. You will have an opportunity to work across the full stack of machine learning solutions - from designing robust and scalable model pipelines to building to deploying the optimized models on Nuro’s fleet of self-driving robots! About The Work
- Optimize Nuro’s autonomy stack with cutting-edge optimization techniques like quantization, low precision inference, and model pruning.
- Work with autonomy engineers to optimize, validate, and deploy large language models.
- Develop and maintain a world-class model compiler framework, FTL.
- Write robust, high-quality software to increase our confidence in our vehicle’s ability to navigate safely on-road.
- Collaborate closely with machine learning domain experts and engineers across behavior, perception and mapping to design and implement end-to-end learned ML solutions.
- 2+ 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 deep learning frameworks (like PyTorch, Jax, Tensorflow, Keras).
- Proficient in Python and working experience with C++.
- You are passionate about accelerating the benefits of robotics for everyday life.
Vacancy posted 5 days ago
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