Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. They are seeking a Software Engineer to join their ML Infrastructure: Dev Enablement Team to build a frictionless development environment for deep learning models in autonomous driving.
Responsibilities:
- Build Agentic AI Tooling: Design, develop, and enhance Agentic AI tools and systems to automate workflows, streamline the ML lifecycle, and empower developer productivity
- Scale Core Infrastructure: Drive the continuous development of our core ML infrastructure and existing CDE platform, leveraging Kubernetes to build robust, high-scale distributed solutions
- System-Level ML Optimization: Partner closely with ML Researchers to profile and optimize distributed training jobs (PyTorch/DDP) and data pipelines. Focus on resolving system-level bottlenecks—such as data loading (I/O), memory management, and network communication overhead—to maximize GPU utilization and training throughput
- Collaborate Cross-Functionally: Partner with ML engineers and data scientists to understand their complex needs, bridging the gap between underlying infrastructure and model development
Requirements:
- BS or MS in Computer Science or related field
- Strong knowledge of software engineering principles and distributed systems
- Strong proficiency with Python or Go or C++
- Experience with building on AWS services or other Cloud platforms and container orchestration using Kubernetes
- Experience with the various stages of the ML development lifecycle
- Hands-on experience with ML model profiling and performance optimization for distributed training
- Experience managing or working with high-performance compute resources (GPUs)
- Experience with ML frameworks such as PyTorch or Ray
- Experience building, integrating, or enhancing Agentic AI systems and LLM-driven developer tools