Senior AI and HPC Observability Engineer

Details

NVIDIA is a pioneer in accelerated computing, known for inventing the GPU and driving breakthroughs in gaming, computer graphics, high-performance computing, and artificial intelligence. Our technology powers everything from generative AI to autonomous systems. Within this mission, the Managed AI Superclusters (MARS) team builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. This role helps design solutions that power advanced computing workloads.

Responsibilities

• Design and scale observability platforms handling high-volume metrics, logs, and traces across distributed environments.
• Build high-performance backend services for telemetry ingestion, processing, and routing.
• Develop and extend OpenTelemetry collectors, processors, exporters, and instrumentation libraries.
• Build and optimize metrics pipelines using large-scale time-series storage systems.
• Design and operate real-time and batch telemetry pipelines using streaming and distributed data technologies.
• Improve platform reliability, performance, and cost efficiency through tuning, capacity planning, and system optimization.
• Develop monitoring, alerting, and service reliability frameworks to ensure platform health and performance.
• Collaborate with platform engineering, infrastructure, and site reliability teams to deliver production-grade observability solutions.

Requirements

• Bachelor’s degree in Computer Science, Computer Engineering, or related field or equivalent experience.
• 5+ years of experience building backend or distributed systems in production environments.
• Strong programming skills in Python, Go, or Java, with experience developing production-quality software.
• Hands-on experience with modern observability architectures, including metrics, logs, and traces.
• Solid experience with PromQL and time-series data systems.
• Experience building or operating distributed data pipelines using technologies such as Kafka, Spark, or Flink.
• Experience working with Kubernetes and cloud-native infrastructure.
• Strong understanding of distributed systems, concurrency, and fault-tolerant system design.
• Strong debugging, performance tuning, and production operations skills.

Ways To Stand Out

• Proven experience designing and scaling observability platforms for AI, GPU, or HPC environments.
• Hands-on expertise with OpenTelemetry, Prometheus, Kafka, and high-volume distributed telemetry pipelines.
• Strong background in data engineering, time-series data modeling, and real-time performance tuning.
• Experience integrating observability with AI/ML pipelines, GPU workload monitoring, or intelligent alerting.
• Demonstrated use of statistical or machine learning techniques for anomaly detection, correlation, or predictive insights.

Compensation

• Base salary range for Level 3: 152,000 USD - 241,500 USD.
• Base salary range for Level 4: 184,000 USD - 287,500 USD.
• You will also be eligible for equity and benefits.

Additional Information

• Applications for this job will be accepted at least until March 6, 2026.
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.
• NVIDIA is an equal opportunity employer and committed to fostering a diverse work environment.