Specter
Fleet Reliability Engineer
San Francisco. Posted 4 months ago
The role
The Fleet Reliability Engineer will build data, analytics, and recovery mechanisms to keep the sensor fleet running. This role involves owning the telemetry and data pipeline to prevent failures from becoming incidents.
What you will do
- Own the fleet reliability data pipeline end to end including telemetry aggregation, storage, and instrumentation.
- Drive down observability cost by owning tooling spend.
- Instrument the fleet and own health metrics that measure reliability.
- Verify that fixes hold fleet-wide.
- Cut alert noise at the source.
- Turn repeat failure patterns into automated detection and recovery.
- Turn fleet telemetry into a live picture of hardware and firmware trends.
- Build failure-mode analysis to inform engineering fixes.
- Own fleet-wide trend and forecasting work including power and solar planning.
- Score reliability work in dollars to prioritize expensive problems.
Required qualifications
- Strong data and software skills in Python (or Go) and SQL.
- Ability to own a data pipeline end to end.
- Hands-on building and tuning observability stacks like OpenTelemetry, Grafana, Prometheus, Datadog, or similar.
- Experience operating physical or embedded device fleets at scale.
- Experience reasoning about how hardware fails in the field.
- Comfortable turning messy field telemetry into trends, failure modes, and forecasts.
- Fluency with databases and data modeling such as PostgreSQL or equivalent.
- Bias toward building mechanisms over doing manual work.
Nice to have
- infrastructure-as-code familiarity (Terraform or similar)
- reliability/SRE fundamentals (SLOs, error budgets, proof-of-recovery) applied to a physical fleet
- experience across the hardware-software boundary — power, connectivity, and physical failure modes
About the company
Specter's mission is to help automate the physical world by building video sensors with state-of-the-art AI agents. The team is small and fast growing with members from Anduril, Tesla, Uber, and the U.S. Special Forces.