About the job
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, and we continue to shape the future of computing through innovation and collaboration. Within this mission, our team, Managed AI Superclusters (MARS) builds and scales the infrastructure, platforms, and tools that enable researchers and engineers to develop the next generation of AI/ML systems. By joining us, you’ll help design solutions that power some of the world’s most advanced computing workloads. Observability is at the heart of this transformation. We are looking for a strong AI & HPC Observability Engineer to build and scale next-generation Observability and Telemetry platforms. You will design and develop high-throughput, reliable telemetry pipelines and modern data infrastructure. This role requires solid distributed systems fundamentals, production-grade coding, and a passion for operational excellence.
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
Qualifications
Minimum
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
Preferred
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