Systems Research Intern, Observability – Summer 2027

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, encouraging environment where everyone is inspired to do their best work. Come join the team and see how we can make a lasting impact on the world!

NVIDIA builds data and observability systems that help engineers understand and operate large-scale services. We are looking for an intern who enjoys both asking foundational questions and building working systems to answer them. Working with observability and data platform engineers, you will study how the field may evolve over the next five years, investigate NVIDIA’s data systems, and turn promising ideas into prototypes, measurements, and clear technical recommendations.

What you’ll be doing:

• Find, read, and critically assess research papers, technical reports, architecture documents, and industry material on observability and large-scale data systems.
• Track the 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 today’s design choices relate to broader changes in storage, compute, query, and telemetry.
• Develop an evidence-based view of possible observability pathways, including which trends appear durable, which remain speculative, and what developments would change your assessment.
• Investigate whether object storage will become more central to observability or whether other architectures may change its role. Evaluate the question across workloads, economics, performance, and operational needs.
• Use AI tools to accelerate discovery, organize sources, and explore competing ideas. Verify important claims against original materials, then develop your own analysis and write original content.
• Write approximately two substantial whitepapers that explain your findings and propose avenues for further research or experimentation. Where possible, choose a focused prototype, benchmark, or analysis to test an important claim.

What we need to see:

• Pursuing a MS or PhD in Computer Science, Computer Engineering or 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 understanding of complex system implementations, to rigorously investigate technical questions.

Ways to stand out from the crowd:

• Technical papers, substantial research reports, 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.
• Experimentation in original, non-traditional, creative writing and willingness to learn quickly, ask questions, and collaborate with cross-functional teams.

NVIDIA is widely considered to be one of the world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the industry working for us. If you're creative and autonomous, we want to hear from you!

You will also be eligible for Intern benefits. ​

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.