Nvidia Senior Observability Engineer AI HPC 

United States, California 

600639138

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/adaptabilityworking 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.