Software Reliability Engineer

Nuro•Mountain View, CA

15h

About The Position

Nuro is seeking a Software Reliability Engineer to join their Robotics Reliability Engineering (RRE) team. This team focuses on fleet reliability as autonomous vehicle capabilities and operating footprint grow. The role involves working across software, hardware, infrastructure, and operations to understand fleet behavior and improve operational readiness. The engineer will coordinate investigations for high-severity events and ensure lessons learned lead to durable platform improvements. This is an opportunity to influence how reliability is engineered into Nuro’s platform as it scales. The role involves building resilient systems through automation, observability, and operational feedback.

Requirements

Experience writing and shipping software that runs in production, with an ownership mindset and attention to how it behaves in real-world conditions.
Ability to build and maintain tools and automation that enable other engineers: internal tools, instrumentation, and visualizations. (Python, Go, Bash, C++)
Strong debugging fundamentals across the stack, including using system signals and live troubleshooting to form hypotheses and identify contributing factors.
Strong interest in reliability engineering as a growth path: you’re motivated by making complex systems understandable, resilient, and easier to run as they scale.

Nice To Haves

Background in distributed systems or real-world deployed systems (vehicles, robotics, IoT, or similar).
Familiarity with production telemetry and observability.
Experience applying reliability metrics and operational feedback loops to drive improvements.
Exposure to cross-team reliability work in mission-critical environments.

Responsibilities

Build fleet-scale pipelines that turn noisy onboard signals into actionable, high-confidence investigations.
Develop automated triage and correlation systems that deduplicate issues, route them to the right owning teams, and attach up-to-date priority signals and diagnostic context.
Partner with engineering teams and subject matter experts to turn investigation outcomes into better instrumentation, automation, and signal quality over time.
Build internal tools and workflows that reduce duplicate effort and increase situational awareness as the fleet scales (self-service debugging, standardized metrics, shared templates, securely scoped access).
Lead reliability investigations to identify contributing factors and ensure learnings turn into durable engineering changes.
Join an on-call rotation to stay close to real-world operations.