About Us:
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.
Responsibilities:
Build reliable tooling components (Python packages, Docker images) and pipelines (Gitlab CI, Databricks) that can be used across the Autonomy team to standardize metrics and store them in a common location.
Gain a deep understanding of how our performance metrics are calculated, ensuring that pairs of leading/lagging metrics use a consistent methodology supported by automated testing.
Propose, design and implement new metrics to close gaps in our evaluation process.
Contribute to the continuous development of tooling (e.g., Cursor and MCP servers) to increase developer velocity and integrate with Rivian systems.
Collaborate closely with colleagues in our offices in California and Serbia, acting as a key technical liaison to gather requirements and drive adoption of the platform.
Demonstrate strong organizational skills to manage multiple projects, meet deadlines, and deliver high-quality results.
Support the team's on-call rotation for any operationally critical systems.
Pay Disclosure:
5+ years of professional software engineering experience, with a significant focus on data engineering.
Strong experience in Python for backend services, data processing, and cloud tooling.
Proficiency in building, testing, and optimizing production-grade data pipelines using tools such as Databricks, Spark (PySpark/Scala), and SQL.
Experience implementing and managing continuous integration and delivery (CI/CD) pipelines (e.g., GitLab CI) and using Docker for containerization.
Experience designing, deploying, and maintaining systems using core AWS services (e.g., S3, EC2, Lambda) and understanding of cloud-native architecture.
Familiarity with autonomous systems development (e.g., perception, planning, control) or relevant domains such as robotics, simulation, or verification/validation.
Proven ability to debug and root-cause issues systematically.
Company Statements:
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