Machine Learning Systems Engineer

About The Company

Motional is a leading autonomous vehicle technology company dedicated to developing innovative solutions that transform transportation safety and efficiency. Committed to pushing the boundaries of AI and machine learning, Motional leverages cutting-edge research and high-performance systems to accelerate the deployment of autonomous vehicles. With a focus on safety, reliability, and scalability, the company collaborates with industry partners and stakeholders to shape the future of mobility. Motional’s diverse team of experts in robotics, software engineering, and AI work together to create impactful solutions that improve lives and redefine transportation standards worldwide.

About The Role

We are seeking a highly skilled Machine Learning Systems Engineer to join our ML Acceleration team. In this pivotal role, you will be responsible for developing and optimizing core systems that enable our researchers to train large-scale models efficiently and effectively. Your primary focus will be on enhancing speed, reducing costs, ensuring system reliability, and increasing throughput for distributed model training. This position offers a unique opportunity to work at the intersection of machine learning research and high-performance systems engineering, directly impacting our ability to scale models and accelerate innovation. You will collaborate closely with research scientists, software engineers, and infrastructure teams to design, implement, and optimize systems that support our cutting-edge AI initiatives, ultimately contributing to the advancement of autonomous vehicle technology.

Qualifications

• Bachelor’s, Master’s, or PhD degree in Computer Science, Computer Engineering, or a related technical discipline
• Strong proficiency in Python programming language
• Extensive hands-on experience with PyTorch framework
• Experience in optimizing machine learning model execution during training and inference
• Deep understanding of machine learning concepts, architectures, and processes
• Proficiency in performance profiling tools such as Nsight and PyTorch Profiler
• Experience with distributed training frameworks like PyTorch Distributed
• Skills in GPU kernel development using Triton or CUDA
• Ability to design and optimize data loading pipelines to maximize throughput
• Exceptional analytical and problem-solving skills with a data-driven approach
• Strong communication and collaboration skills

Responsibilities

• Utilize profiling tools to identify bottlenecks in data loading, gradient computation, and communication processes
• Implement performance optimizations such as kernel fusion, sharding, and tiling to improve training step times
• Optimize distributed training pipelines to enhance scalability and efficiency
• Design, develop, and maintain high-performance GPU kernels in Triton or CUDA for advanced ML workloads
• Engineer robust data pipelines to ensure high training throughput and system reliability
• Collaborate with research teams to understand system requirements and translate them into scalable solutions
• Continuously analyze system performance metrics and implement improvements
• Contribute to the development of best practices for high-performance ML systems engineering

Benefits

• Competitive salary range of $144,000 to $192,000 USD
• Comprehensive health benefits including medical, dental, and vision insurance
• 401(k) plan with company matching contributions
• Health savings accounts (HSAs) and flexible spending accounts (FSAs)
• Life insurance and pet insurance options
• Opportunities for professional growth and development
• Flexible work arrangements including hybrid and remote options
• Inclusive and diverse work environment committed to equity and inclusion

Equal Opportunity

Motional is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. All qualified applicants will receive consideration for employment. To comply with Federal Law, we participate in E-Verify, a system that verifies the employment eligibility of all new hires.