Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Grafana @ 7
Kubernetes @ 4
SQL @ 7
Spark @ 4
Distributed Systems @ 4
Leadership @ 4
Communication @ 4
SRE @ 4
BI @ 4
Databricks @ 7
Reporting @ 4
GPU @ 4
Observability @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
As a Senior Technical Program Manager with a passion for data-driven operations, you will lead the DGX Cloud Fleet Health reporting program — delivering real-time, actionable insights on the availability and reliability of our GPU fleet. A core focus of this role is advancing Mean-Time-Between-Interruption (MTBI): understanding the root causes of fleet interruptions, surfacing patterns in the data, and driving cross-functional programs to measurably extend fleet uptime. You will partner closely with Capacity Operations, Infrastructure, SRE, and Engineering teams to translate complex fleet signals into decisions that directly improve customer experience.
Responsibilities
- Define and own the metrics framework for measuring fleet health, reliability, and MTBI across a diverse and rapidly scaling GPU fleet.
- Lead hands-on data investigations — querying telemetry, correlating failure signals, and building statistical models — to identify the root causes of interruptions and quantify their impact.
- Own and drive execution of cross-functional MTBI improvement programs end-to-end — from translating analytical findings into a prioritized roadmap, to holding teams accountable to milestones and delivering measurable reliability gains.
- Build and maintain dashboards, automated anomaly detection, and alerting frameworks that surface gaps in fleet health reporting in real time.
- Anticipate and close reporting gaps with new cloud providers and hardware platforms by working closely with Infrastructure bring-up teams.
- Communicate complex data findings and program status clearly to senior leadership, turning raw signals into crisp narratives and recommendations.
Requirements
- 8+ years of Technical Program Management experience, with at least 3 years in infrastructure, platform, or reliability-focused domains.
- Strong hands-on data analytics skills — comfortable writing SQL, working with large telemetry datasets, and building dashboards (Grafana, Superset, Databricks, or equivalent).
- Demonstrated ability to define and operationalize reliability metrics (MTBI, MTTR, availability SLAs) and drive engineering teams toward measurable improvements.
- Proven ability to lead deep-dive investigations across ambiguous, multi-system problems and translate findings into long-term solutions.
- Excellent executive communication skills — able to distill complex technical findings into clear, decision-ready narratives for senior leadership.
- MS in EE, CS, or equivalent experience.
Ways to stand out from the crowd (Preferred)
- Familiarity with NVIDIA GPU architectures and DGX/HGX infrastructure.
- Experience with Databricks, Apache Spark, or other large-scale data processing platforms.
- Hands-on experience with Grafana, Superset, or similar observability/BI tooling.
- Background in cloud-native infrastructure, Kubernetes, or large-scale distributed systems.
Compensation & Additional details
- Base salary ranges: 168,000 USD - 258,750 USD for Level 4; 200,000 USD - 322,000 USD for Level 5.
- You will also be eligible for equity and benefits.
- Applications for this job will be accepted at least until July 4, 2026.
- This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate on the basis of protected characteristics.