About The Position

Rivian’s Autonomy organization is looking for a Staff Software Engineer, ML Applications on the Data & Cloud team. You will set the direction for large-scale applications and data pipelines that power data annotation, ML/DL training and infrastructure, using modern cloud services and open-source frameworks. You will tackle ambiguous, cross-functional problems (scale, reliability, cost, developer velocity) and align engineering, ML, and data partners on architecture and roadmaps. You will help the Autonomy organization move faster by building reliable, observable software on top of petabyte-scale sensor datasets.

Requirements

  • B.S., M.S., or Ph.D. in Computer Science or a related field and at least 6 years of relevant experience; or at least 8 years of industry experience without a degree.
  • Strong full-stack background with TypeScript and modern web stacks (React preferred); track record shipping and evolving complex internal web applications.
  • Deep backend expertise in Python, Go, or Java on high-throughput or large-data systems.
  • Demonstrated success leading technical design for multi-service or platform-scale systems.
  • Hands-on experience with MongoDB, Postgres, and/or similar databases in production.
  • Proven ability to work cross-functionally across teams and domains, and to communicate clearly to technical and non-technical leaders.
  • History of mentoring engineers and improving team-wide engineering practices.

Nice To Haves

  • Familiarity with end-to-end ML workflows and the production lifecycle of ML data (ingestion, labeling, training, evaluation).
  • Experience with AWS, MLOps, and data/ML pipelines in cloud environments.

Responsibilities

  • Lead the technical development of Rivian’s in-house 2D and 3D labelling platform, enabling the delivery of high quality data for model training and validation.
  • Set full-stack platform direction (TypeScript, React) for internal tools that accelerate annotation and ML workflows.
  • Lead alignment on backend services and APIs (Go/Python) across teams; establish standards for APIs, data contracts, and service boundaries.
  • Guide data modeling and storage strategy across NoSQL databases like MongoDB, including performance, cost and consistency tradeoffs at scale.
  • Partner with architects, ML engineers, and data engineers on requirements, architecture and design.
  • Drive cloud cost, performance, and reliability initiatives; champion SLOs, observability, and incident learning.
  • Mentor junior engineers with technical leadership and knowledge.

Benefits

  • paid vacation
  • paid sick leave
  • life insurance
  • medical insurance
  • dental insurance
  • vision insurance
  • short-term disability insurance
  • long-term disability insurance
  • 401(k) Plan
  • Employee Stock Purchase Program
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