Software Engineer - ML Development Enablement

About the Role

Join our ML Infrastructure Dev Enablement team as a Senior Software Engineer working to create a seamless development environment that empowers research and engineering teams to quickly innovate with deep learning models for autonomous vehicles. Our team manages a large-scale Cloud Development Environment (CDE) platform that delivers standardized, high-performance workspaces for machine learning development.

As part of this role, you'll lead key initiatives such as designing multi-cloud environments to optimize GPU resource availability, advancing model optimization efforts, and developing next-generation Agentic AI tools. Your contributions will ensure our training ecosystem remains at the forefront — robust, efficient, and resilient.

Key Responsibilities

• Design and implement multi-cloud infrastructure solutions to enhance scalability and reliability of GPU compute resources for ML training.
• Work with ML researchers to analyze and optimize distributed training workloads (using PyTorch/DDP), addressing system bottlenecks related to data input/output, memory handling, and network latency aiming to maximize GPU usage and throughput.
• Create and improve Agentic AI tooling to automate workflows, streamline machine learning lifecycles, and boost developer productivity.
• Enhance core machine learning infrastructure and the existing CDE platform by building scalable, distributed systems primarily using Kubernetes.
• Collaborate cross-functionally with ML engineers and data scientists, bridging infrastructure and model development needs.
• Promote engineering best practices including software quality, reliability, and mentor junior colleagues via design guidance and code reviews.

Qualifications and Skills

• Bachelor’s or Master’s degree in Computer Science or related disciplines.
• Five or more years of professional software engineering experience, particularly with distributed systems.
• Proficiency in programming languages such as Python, Go, or C++.
• Strong experience with AWS or other cloud platforms and expertise in container orchestration with Kubernetes.
• Familiarity with machine learning development processes end-to-end.
• Excellent communication skills and proven ability to take ownership of infrastructure and mentor team members.

Preferred Extras

• Practical experience profiling and optimizing ML models for distributed training environments.
• Hands-on with high-performance GPU compute management.
• Knowledge of ML frameworks such as PyTorch or Ray.
• Experience with developing or integrating Agentic AI and large language model based developer tools.

About Motional

Motional is at the forefront of autonomous vehicle technology, committed to making driverless cars safe, dependable, and accessible. Our mission transcends technology, focusing on creating safer roads, equitable transportation, and enriching communities. We value diversity, strive for an inclusive work culture, and believe diverse perspectives drive innovation.

We operate globally with headquarters in Boston and vital operations across the U.S and Asia. Having pioneered significant milestones like the first fully autonomous cross-country drive and the launch of the world’s first robotaxi pilot, we are scaling rapidly towards commercializing our technology.

Diversity and Compliance

Motional is an Equal Opportunity Employer that celebrates diversity. We ensure inclusive environments where everyone feels valued. We comply with all Federal laws including E-Verify for employment eligibility verification.