Jobs · Engineering · California

Staff Software Engineer, ML Data Infrastructure, Autonomy

Rivian · Palo Alto, CA · 1 mo ago
On-siteEngineering$207k–$258k/yrFull-time

About the role

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions-free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract. As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Rivian's Autonomy org needs a Staff Software Engineer, ML Data Infrastructure to own how autonomy data is described, indexed and accessed. This sits in the Platform Services team in the AI Platform organization in the Autonomy team. Our fleet of 100,000+ vehicles produces a continuous stream of multi-modal drive data, plus the output of every model run against it and every simulation executed on it. The role requires deep expertise in columnar and analytical data stores, schema and format design, and the query and access layers that ML and analytics teams depend on. You'll work with the AI Platform, Perception, Planning, Simulation, and Vehicle Integration, Product Management, and other technology partners. Autonomy data currently lives across multiple systems because no single store serves all our access patterns: fleet-scale byte storage, petabyte-scale analytics, sub-second fleet-wide search, and small transactional state each have different cost and latency profiles. You'll own the unified metadata and query layer, decide what consolidates and what stays specialized, and land the migrations onto a unified data lake.

Responsibilities

  • Own the unified data layer for autonomy: a single interface over document metadata, high-cardinality columnar analytics, real-time search, and object-stored sensor payloads, so engineers query concepts rather than databases.
  • Design the

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