Note: The job is a remote job and is open to candidates in USA. Motional is a driverless technology company developing autonomous vehicles. The Machine Learning Systems Engineer will build and optimize core systems for large-scale distributed model training, focusing on speed, cost, reliability, and throughput. The role involves performance profiling, distributed training optimization, GPU kernel development, and data pipeline engineering.

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

Skills

• 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
• We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote

Benefits

• Candidates for certain positions are eligible to participate in Motional’s benefits program.
• Medical
• Dental
• Vision
• 401k with a company match
• Health saving accounts
• Life insurance
• Pet insurance
• Hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas, or fully remote

Company Overview

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