Senior AI and HPC Observability Engineer

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.

What You Will Be Doing:

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

What We Need to see:

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 from The Crowd:

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

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits .

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 committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.