Systems Research Intern, Observability – Summer 2027

NVIDIA•Santa Clara, CA

1d•$20 - $94

About The Position

NVIDIA is seeking a Systems Research Intern to investigate the future of observability and large-scale data systems. Working with observability and data platform engineers, the intern will study NVIDIA’s relevant systems and assess how the field may evolve over the next five years. The work combines technical research with practical investigation, turning promising ideas into prototypes, measurements, and technical recommendations. The intern will examine research papers, technical reports, architecture documents, and industry materials; track potentially significant ideas and organizations; and relate NVIDIA’s current design choices to broader developments in storage, compute, query, and telemetry. The role includes developing an evidence-based assessment of possible observability pathways, evaluating the potential role of object storage across workloads, economics, performance, and operational needs, and using AI tools to support research while verifying important claims against original sources. The intern will write approximately two substantial whitepapers presenting findings and proposing further research or experimentation. Where possible, the intern will also choose a focused prototype, benchmark, or analysis to test an important claim. This is a Summer 2027 internship. The expected hourly rate is $20–$94, and the intern is eligible for intern benefits.

Requirements

Pursuing an MS or PhD in Computer Science, Computer Engineering, or an equivalent program area.
Experience finding and synthesizing technical literature, evaluating competing claims, and producing clear written analysis through coursework, research, or projects.
Coursework or project experience in distributed systems, databases, storage, networking, or cloud computing.
Advanced programming experience and an understanding of complex system implementations sufficient to rigorously investigate technical questions.

Nice To Haves

Technical papers, substantial research reports, or other writing that turns complex systems material into a clear argument.
Interest in how observability, data platforms, and infrastructure may evolve as AI and large-scale computing change their workloads.
Experience with OpenTelemetry (logs, metrics, tracing), object storage, data lakes, and query engines.
A record of forming independent technical judgments, identifying uncertainty, and revising a position when new evidence warrants it.
Experience experimenting with original, non-traditional, creative writing.
Willingness to learn quickly, ask questions, and collaborate with cross-functional teams.

Responsibilities

Find, read, and critically assess research papers, technical reports, architecture documents, and industry material on observability and large-scale data systems.
Track ideas and organizations that may signal meaningful shifts in the field.
Study NVIDIA’s relevant data and observability systems through documentation and conversations with engineers.
Identify how current design choices relate to broader changes in storage, compute, query, and telemetry.
Develop an evidence-based view of possible observability pathways, distinguishing durable trends from speculative ones and identifying developments that could change the assessment.
Investigate whether object storage will become more central to observability or whether other architectures may change its role, evaluating workloads, economics, performance, and operational needs.
Use AI tools to accelerate discovery, organize sources, and explore competing ideas; verify important claims against original materials and develop independent analysis and original content.
Write approximately two substantial whitepapers explaining findings and proposing avenues for further research or experimentation.
Where possible, conduct a focused prototype, benchmark, or analysis to test an important claim.