Principal Software Engineer, At-Scale Reliability and Fleet Intelligence — CSP Engagements
Listed on 2026-07-03
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Software Development
DevOps
We're looking for a Principal Software Engineer to join our CSP Engagements team as the technical focal point for fleet-scale reliability, working directly with engineering teams of key CSP / hyperscale customers to ensure NVIDIA platforms achieve target MTBI (Mean Time Between Interruptions) in production. In this role, you will augment NVIDIA's internal software/firmware and quality teams with a dedicated CSP-facing focus.
You will drive work streams with CSP engineering teams to build shared understanding of reliability software/firmware architecture, methodology, incorporate their fleet telemetry and failure data into NVIDIA's improvement priorities, and validate that reliability improvements measured in the lab translate to real customer environments. Your cross-CSP visibility enables you to distinguish systemic architectural gaps from environmental or configuration-specific issues that no single customer engagement could identify alone.
you'll be doing:
- Drive reliability work streams with CSP engineering teams — ensuring shared understanding of MTBI measurement methodology, failure classification, and health monitoring architecture
- Gather and synthesize CSP fleet reliability data — identify failure patterns that appear across multiple customers and champion improvements back into NVIDIA's firmware, driver, and hardware teams
- Define consistent MTBI measurement methodology that works across different CSP monitoring environments and operational practices
- Conduct fleet-scale failure pattern analysis using statistical methods (Pareto, survival analysis, Weibull) to classify failures as systemic, environmental, or configuration-specific
- Drive fleet health monitoring integration architecture — ensure NVIDIA's health agents, telemetry, and reporting align with CSP operational workflows and automation
- Define burn‑in reliability test environment and cluster certification criteria in collaboration with quality teams, validating with customers that criteria are meaningful
- Collaborate with CSPs to ensure reliability‑related integration work (health monitoring deployment, telemetry pipeline, alerting configuration) is complete ahead of at‑scale launch
- Develop predictive failure models using fleet telemetry and validate their effectiveness in customer environments
- 15+ years of experience in systems software at datacenter scale, or reliability engineering with focus on at‑scale challenges.
- BS or MS in Computer Science, Electrical Engineering, Statistics, or related field (or equivalent experience)
- Deep expertise in multi‑NUMA, rack‑scale system software and firmware. Statistical failure analysis methods: MTBF/MTBI calculation, Pareto analysis, root cause classification
- Experience with fleet‑level telemetry and observability systems: time‑series databases, anomaly detection, health scoring, event correlation
- Understanding of hardware failure modes in large‑scale GPU/accelerator deployments — ability to classify and prioritize across compute, interconnect, memory, power, and thermal domains
- Experience defining or operating burn‑in, stress testing, or certification frameworks for complex hardware systems. Familiarity with predictive maintenance or anomaly detection approaches applied to fleet health data
- Customer obsession — genuine passion for understanding fleet reliability challenges at scale and translating them into actionable engineering priorities
- Strong communication — ability to present statistical reliability findings to both deep technical audiences and executive leadership. Demonstrated success driving cross‑functional improvements across hardware, firmware, and software teams without direct authority
- Experience in fleet reliability at a hyperscaler (hardware health, fleet reliability at leading CSP/Hyperscaler)
- Familiarity with NVIDIA GPU error taxonomy (Xid errors, NVLink error counters, thermal events, CPER records)
- Experience building health scoring or predictive failure models for accelerator or HPC infrastructure
- Background in defining MTBI/MTBF measurement standards or certification programs for complex multi‑component systems
- Understanding of how…
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