NVIDIA’s Hardware Infrastructure organization is seeking a Senior or Principal Data and Observability Architect. We serve and collaborate directly with NVIDIA’s rapidly growing AI, HW, and SW engineering and research teams across the company. We are looking for a technical leader to define a vision and roadmap for distributed observability systems for large-scale AI and HPC clusters and workloads and guide implementation towards this vision. You will architect systems for data collection, aggregation, enrichment, storage, retrieval, and visualization to spectacularly improve efficiency, performance, and productivity of AI and HPC workloads. You will lead technical teams to develop, deploy, and operate observability solutions for multiple compute clusters around the world.
What You’ll Be Doing:
Collaborate with AI, HW, and SW engineering and research teams to define a vision and roadmap for AI/HPC cluster observability.
Architect and lead teams to develop, test, and deploy data collectors, pipelines, visualization and retrieval services.
Define data collection and retention polices 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 designing and building 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
Technical lead level 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
12+ years of relevant 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 in 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.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Last updated: 23 hours ago
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