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Nuro

Senior/Staff ML Engineer, AI-Assisted Efficiency Optimization

Reposted 3 Days Ago
In-Office
Mountain View, CA
194K-352K Annually
Senior level
In-Office
Mountain View, CA
194K-352K Annually
Senior level
Lead GenAI-assisted GPU kernel optimization projects to improve efficiency and reduce inference latency using advanced AI technologies and collaboration with teams.
The summary above was generated by AI

Who We Are 

Nuro is a self-driving technology company on a mission to make autonomy accessible to all. Founded in 2016, Nuro is building the world’s most scalable driver, combining cutting-edge AI with automotive-grade hardware. Nuro licenses its core technology, the Nuro Driver™, to support a wide range of applications, from robotaxis and commercial fleets to personally owned vehicles. With technology proven over years of self-driving deployments, Nuro gives the automakers and mobility platforms a clear path to AVs at commercial scale—empowering a safer, richer, and more connected future.

About the Role

We are looking for an experienced, goal-oriented Machine Learning Engineer to lead our GenAI-assisted GPU kernel optimizations project delivery. This project stands to serve the dual objectives of improving maximum flop utilization and reducing inference latency, to surpass human-engineered performance through the application of advanced AI technologies.

About the Work

  • Implement AI-driven methods for GPU kernel optimizations to enhance program efficiency and performance leveraging tools such as CompilerGym, KernelLLM, etc.
  • Develop strategies for resource-efficient deployment of intelligent optimization processes using frameworks such as AutoFDO.
  • Guide high-level optimizations that include both highly optimized kernels, as well as AI-driven neural architecture search (NAS) to optimize training efficiency and inference latency.
  • Assess performance improvements via evaluation metrics and real-world feedback.
  • Collaborate with internal teams to benchmark processes and strategies for future AI-assisted optimizations.
  • Utilize state-of-the-art leaderboard scoring systems to test the ability of different AI models to generate efficient GPU kernels.
  • Stay current with industry advances.

About You

  • Bachelor's or Master's Degree in Computer Science, Engineering, or a related field.
  • Extensive experience with AI models, including but not limited to LLMs.
  • Strong understanding of retrieval-augmented generation (RAG) and Language Models (LLMs).
  • Ability to self-motivate, undertake complex assignments independently, and while enjoying to balance innovative exploration with practical considerations.

Bonus Points 

  • Experience with GPU programming, CUDA, Triton, and Machine Learning algorithms.
  • Familiarity with optimization techniques such as neural architecture search (NAS).
  • Hands-on experience with optimization programs, such as Google's AutoFDO.

At Nuro, your base pay is one part of your total compensation package. For this position, the reasonably expected base pay range is between $193,930 and $352,290 for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. In the event that you are considered for a different level, a higher or lower pay range would apply. This position is also eligible for an annual performance bonus, equity, and a competitive benefits package.

At Nuro, we celebrate differences and are committed to a diverse workplace that fosters inclusion and psychological safety for all employees. Nuro is proud to be an equal opportunity employer and expressly prohibits any form of workplace discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other legally protected characteristics. #li-dnp

Top Skills

AI
Autofdo
Compilergym
Cuda
Gpu
Kernelllm
Machine Learning
Triton

Nuro Mountain View, California, USA Office

Mountain View, CA, United States

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