Senior AI and HPC Observability Engineer

NVIDIA•Santa Clara, CA

7d•$152,000 - $287,500

About The Position

NVIDIA’s Managed AI Superclusters (MARS) team builds and scales infrastructure, platforms, and tools that enable researchers and engineers to develop AI/ML systems. The Senior AI and HPC Observability Engineer will build and scale next-generation observability and telemetry platforms, designing reliable, high-throughput telemetry pipelines and modern data infrastructure. The role calls for distributed systems expertise, production-quality software development, and a focus on operational excellence.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
At least 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.

Nice To Haves

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.

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.