Principal Data Platform Architect

NVIDIA • Santa Clara, CA

248d • $272,000 - $425,500

About The Position

NVIDIA’s Hardware Infrastructure organization is seeking a Principal Data Platform 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 data platform and 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.

Requirements

• 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, JS and Java programming experience.
• Thorough understanding of databases (relational and non-relational).
• 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.
• 15+ years of relevant experience.

Nice To Haves

• 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.

Responsibilities

• 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 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.

Benefits

• Equity and benefits.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Master's degree
• Number of Employees: 5,001-10,000 employees