Machine Learning Systems Engineer

Motional is a driverless technology company developing autonomous vehicles to make transportation safer, more reliable, and accessible. The Machine Learning Systems Engineer will build and optimize the core systems supporting large-scale distributed model training, focusing on performance, cost, reliability, and throughput.

Responsibilities:

• Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time
• Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed
• Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads
• Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput

Requirements:

• Bachelor's, Master's degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline
• Strong proficiency in Python
• Extensive hands-on experience with PyTorch
• Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes
• Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges