Rivian is seeking a Staff Software Engineer to join their ML Infrastructure team, which focuses on building a reliable training platform for autonomous driving models. The role involves designing and constructing various layers of the platform, including job scheduling, storage, observability, and the training framework. The engineer will work closely with model training teams and other infrastructure teams to optimize performance and ensure efficient resource utilization. This position is ideal for someone looking to set technical direction and contribute to a rapidly evolving environment.

• 5+ years of software engineering experience with substantial distributed-systems work in production.
• Experience building or operating large-scale compute or ML infrastructure.
• Deep expertise in cluster scheduling and multi-tenancy, particularly with Kubernetes-based scheduling.
• Strong programming skills in Python and experience with at least one additional relevant language such as Go, Rust, or C++.
• Experience operating on a major cloud provider, preferably AWS, and on Kubernetes.

• Evolve the control plane into a single entry point for every accelerator cluster across cloud providers.
• Design scheduling that maximizes fleet goodput and implements fair sharing across teams.
• Develop the storage tiering between object storage, caches, and memory to optimize request patterns.
• Build monitoring and profiling tools to provide visibility into job performance across all layers.
• Define the platform roadmap and collaborate with ML engineers to identify and resolve bottlenecks.

• Employees at Rivian are often offered comprehensive health, dental, and vision insurance, a 401(k) with company match, ESPP and potential RSU grants, performance bonuses, and generous time off including paid parental and sick leave. Perks can include 24/7 mental-health coaching and therapy, Hinge Health for Anthem enrollees, tuition assistance and professional development, plus on-site food and a wide range of employee discounts on items like computers, mobile phones, home loans, and pet care.