Senior Observability Engineer, AI and HPC

NVIDIA’s Hardware Infrastructure organization is seeking a Senior Observability Engineer to help architect and implement our distributed observability systems for AI and HPC clusters. We serve and collaborate directly with NVIDIA’s rapidly growing AI, HW, and SW engineering and research teams across the company. You will be working with a team of dedicated engineers on systems for data collection, aggregation, enrichment, storage, retrieval, and visualization to spectacularly improve efficiency, performance, and productivity of AI and HPC workloads. You will develop, deploy, and operate observability solutions for multiple compute clusters around the world.
 

What You’ll Be Doing:

• Collaborate with AI, HW, SW engineering and research teams to deliver observability solutions that meet their needs in AI/HPC clusters.

• Develop, test, and deploy data collectors, pipelines, visualization and retrieval services.

• Define data collection and retention policies to balance network bandwidth, system load, and storage capacity costs with data analysis requirements.

• Work in a diverse team to provide operational and strategic data to empower our engineers and researchers to improve performance, productivity, and efficiency.

• Continuously improve quality, workloads, and processes through better observability.

What We Need to See:

• Experience developing large scale, distributed observability systems.

• Ability to collaborate with data scientists, researchers, and engineering teams to identify high value data for collection and analysis.

• Experience with turning raw data into actionable reports

• Experience with observability platforms such as Apache Spark, Elastic/Open Search, Grafana, Prometheus, and other similar open-source tools

• Python programming experience and use of API calls

• Passion for improving the productivity of others

• Excellent planning and interpersonal skills

• Flexibility/adaptability working in a dynamic environment with changing requirements

• MS (preferred) or BS in Computer Science, Electrical Engineering, or related field (or equivalent experience)

• 8+ yrs of proven experience.

Ways To Stand Out from The Crowd:

• Background in computer science, machine learning, deep learning, open-source software, infrastructure technologies, and GPU technology.

• Prior experience in infrastructure software, production application software development, software development, release and support methodology and DevOps

• Experience in the management of datacenters and large-scale distributed computing

• Experience working with AI researchers and/or EDA developers

• Consistent track record of driving process improvements and measuring efficiency and a passion for sharing knowledge and experience driving complex projects end-to-end.