Senior/Staff ML Engineer, AI-Assisted Efficiency Optimization at Nuro LLC

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

28 Jan, 26

Salary

352290.0

Posted On

30 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Models, GPU Programming, CUDA, Triton, Optimization Techniques, Neural Architecture Search, AutoFDO, CompilerGym, KernelLLM, Inference Latency, Performance Metrics, Benchmarking, Resource Efficiency, Self-Motivation, Complex Assignments

Industry

Software Development

Description

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

Responsibilities

Lead the GenAI-assisted GPU kernel optimizations project delivery. Implement AI-driven methods to enhance program efficiency and performance.