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Rivian

Makes electric pickups, SUVs and delivery vans

Senior Software Engineer - Autonomy Evaluation & Metrics Platform

Backend EngineeringPosted on Nov 12
Full-timePalo Alto, CA, USA$179k - $223.8kIn-person

About the Job

Requirements

  • At least 5 years of professional software engineering experience, or equivalent demonstrated experience and impact, including ownership of production backend or data-intensive systems.
  • Hands-on experience building software for autonomy or robotics, with direct exposure to evaluation, simulation, perception, planning, or validation workflows.
  • Strong Python programming skills, including writing, testing, profiling, and debugging maintainable production software.
  • Practical SQL skills, including validating query logic, results, and performance; AI coding tools are expected to support writing and refining queries.
  • Demonstrated system-design ability across service APIs, data modeling, distributed processing, and storage, including failure recovery, consistency, and performance trade-offs.
  • Experience taking a project from requirements and design through implementation, rollout, and operation, coordinating dependencies and communicating trade-offs clearly.
  • Practical understanding of model inference and evaluation, including held-out datasets, generalization, reproducibility, model versioning, and the differences between open-loop replay, closed-loop simulation, and real-world measurements.
  • Ability to reason about sampling, confidence intervals, noisy metrics, and valid comparisons, and to work with domain experts when stronger statistical analysis is needed.
  • Experience with cloud infrastructure, containers, CI/CD, and production observability, plus constructive code review and mentoring.

Responsibilities

  • Own the design and delivery of a metrics-platform area, such as the metric registry, computation services, or comparison and reporting APIs, in partnership with the team’s technical lead.
  • Design versioned metric definitions and data models for inputs, aggregation, slicing, and results, preserving provenance that links official evaluation runs to code, model, dataset, and scenario versions.
  • Build distributed computation and storage paths with idempotent execution, incremental processing, and controlled backfills, balancing throughput, latency, cost, and reproducibility.
  • Build comparison tools that expose coverage, sample sizes, uncertainty, and changes in evaluation inputs, helping users distinguish model regressions from data, simulator, or infrastructure failures.
  • Partner with model developers to design evaluation experiments, inspect predictions, and analyze failure patterns; use findings to guide model and data improvements and build reusable evaluation harnesses that shorten the iteration cycle.
  • Integrate metrics and regression checks into replay and closed-loop evaluation workflows and CI; partner with domain owners on metric semantics and thresholds and with Systems on evidence for release decisions.
  • Deliver self-service APIs and scorecards backed by consistent definitions and results, and migrate existing consumers incrementally while preserving reporting continuity and traceability.
  • Own reliability and performance for services through testing, observability, incident investigation, and operational documentation; measure improvements in turnaround time, correctness, and cost.
  • Write and review production code, lead design reviews for projects, mentor engineers, and collaborate across Palo Alto, London, and Belgrade to deliver software that users adopt.

Desired Qualifications

  • Experience building metric registries, evaluation services, experiment-tracking systems, or automated regression gates used by multiple engineering teams.
  • Experience with Spark, Databricks, Delta Lake, or comparable distributed data systems, and with AWS, Docker, or GitLab CI.
  • Experience migrating analytical or reporting systems without breaking downstream consumers, or linking metrics to scenario-level debugging and triage.
  • Experience with PyTorch or similar machine-learning frameworks, evaluation of end-to-end driving models, or connecting offline model metrics to closed-loop and real-world driving behavior.

About the Company

Rivian

Makes electric pickups, SUVs and delivery vans

Rivian designs and builds electric pickup trucks, SUVs, and delivery vans, pairing off-road ability with electronics and software it develops itself. In 2021, its R1T became the first fully electric pickup truck on the US consumer market, ahead of larger rivals such as Ford and Tesla. It makes the R1T pickup, the R1S and R2 SUVs, and commercial vans in Normal, Illinois, and sells them directly online and in its own stores rather than through dealers. Its vehicles run on Rivian's own software, which gains features through updates sent over the internet, and most revenue comes from vehicle sales, with service and optional software adding more. Rivian was founded in 2009 and is based in Irvine, California.

Company size
10,001+
Company stage
IPO
Headquarters
Irvine, CA
Founded
2009

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