Senior/Staff Machine Learning Engineer, Nuro

• B.S./M.S./Ph.D. in Computer Science, Electrical Engineering, or related technical field (or equivalent experience)
• 4+ years of professional experience in ML infrastructure, distributed training, or ML systems engineering, scaling models on multi-node, multi-accelerator clusters
• Understanding of training, evaluation, and distillation workflows for billion-parameter models
• Expert-level knowledge in distributed systems and (remote) Python
• Strong skills in profiling, debugging, and optimizing quantized workloads
• Experience with ML compilers and strategies to reduce startup overhead
• Familiarity with model distillation and efficient inference workflows

Desirable

• We are seeking a highly experienced Staff Software Engineer to join our ML Infrastructure team, focusing on optimizing training runtime efficiency and input pipelines for model training, evaluation, and distillation workloads
• In this role you will enable models to train faster and more efficiently – accelerating our self-driving roadmap of commercial and personal mobility
• In this role you will contribute to the overall ML Infrastructure strategy, particularly in areas related to runtime efficiency and goodput
• Collaborate with ML practitioners and other infrastructure teams to understand their needs and integrate optimized input pipelines seamlessly into their workflows
• Detect, diagnose, and resolve performance bottlenecks across training, eval, and model distillation workflows
• Optimize training performance, resource utilization, and ensure consistent, reproducible model training outcomes
• Optimize input data pipelines to increase runtime goodput, ensuring accelerators maximize their "time on task" and minimize idle cycles
• Champion best practices for robust, reproducible, and debuggable ML experimentation