A Machine Learning Engineer role focused on developing AI-driven GPU kernel optimizations to improve performance and reduce inference latency, supporting Nuro's autonomous driving technology.
Key Responsibilities
Implement AI-driven GPU kernel optimization methods to improve program efficiency and performance.
Develop strategies for resource-efficient deployment of AI-based optimization processes.
Guide high-level optimizations, including neural architecture search, to enhance training efficiency and inference latency.
Assess performance improvements using evaluation metrics and real-world feedback.
Collaborate with internal teams to benchmark and refine AI-assisted optimization strategies.
Utilize leaderboard scoring systems to evaluate AI model effectiveness in generating efficient GPU kernels.
Requirements
Bachelor's or Master's Degree in Computer Science, Engineering, or a related field.
Extensive experience with AI models, including but not limited to Large Language Models (LLMs).
Strong understanding of retrieval-augmented generation (RAG) and Language Models (LLMs).
Ability to self-motivate, undertake complex assignments independently, and balance innovative exploration with practical considerations.
Benefits & Perks
Compensation/salary range between $193,930 and $352,290 depending on experience and qualifications