ashby
Fleet Reliability Engineer
Specter
San Francisco, USA
Full-time
Mid
Onsite
Discovered 1 weeks ago
PythonGoSQLOpenTelemetryGrafanaPrometheus
Free
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Responsibilities:
- Reliability Data Platform — Primary
- Own the fleet’s reliability data pipeline end to end: telemetry aggregation, storage, and instrumentation.
- Drive down observability cost — own the tooling spend and cut what we pay for but don’t use.
- Instrument the fleet and own the health metrics that measure reliability.
- Proof-of-Recovery & Alert Hygiene
- Verify that fixes hold fleet-wide, not just on the device that paged.
- Cut alert noise at the source — separate real failures from self-resolving ones.
- Turn repeat failure patterns into automated detection and recovery.
- Fleet Health & Failure-Mode Analytics
- Turn fleet telemetry into a live picture of which cohorts, hardware revisions, and firmware versions are trending toward failure, and why.
- Build the failure-mode analysis that tells engineering what to fix at the source.
- Own fleet-wide trend and forecasting work, including power and solar planning.
- Reliability Economics & Prioritization
- Score reliability work in dollars — field-trip cost, hardware-return cost, observability spend — and prioritize the most expensive problems first.
- Set and track the fleet’s reliability targets: uptime, offline rate, truck-rolls per sensor-year.
- Give the team the data to make reliability-versus-cost tradeoffs.
Qualifications:
- Strong data and software skills — Python (or Go) and SQL — and the ability to own a data pipeline end to end.
- Hands-on building and tuning observability stacks (OpenTelemetry, Grafana, Prometheus, Datadog, or similar), including their cost.
- Experience operating physical or embedded device fleets at scale, and reasoning about how hardware fails in the field.
- Comfortable turning messy field telemetry into trends, failure modes, and forecasts.
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