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Systems Performance Engineer, Agentic AI Workloads – New College Grad 2026

NVIDIANVIDIA·Semiconductors

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About the role

NVIDIA is looking for a Deep Learning Architect to join our team working at the cutting edge of AI infrastructure. As agentic LLM workloads reshape the demands placed on modern datacenters, we need engineers who can model, simulate, and reason about complex system-level traffic at scale. If you have a passion for performance analysis, a strong quantitative foundation, and excitement about the future of AI systems, we'd love to talk.


In this role, you will build and run simulations that capture the traffic dynamics of agentic AI workloads, mine the results for actionable insights, and help guide architectural decisions for next-generation datacenter and GPU systems.

What you'll be doing:

  • Develop and extend C++ and Python simulators that model system-level network and compute traffic for agentic LLM workloads in datacenter environments

  • Characterize real-world LLM serving workloads and distill them into representative simulator inputs

  • Run simulations at scale and apply statistical techniques to post-process and interpret results

  • Identify performance bottlenecks and translate findings into concrete architectural recommendations

  • Collaborate with hardware, software, and research teams to influence the design of future AI systems

What we need to see:

  • Pursuing or recently completed a MS, or PhD in CS, EE, Mathematics, or a related field (or equivalent experience)

  • Strong programming skills in C++ and Python

  • Solid foundations in queueing theory and traffic modeling (e.g., Erlang models, Little's Law)

  • Strong statistics background: characterize huge datasets with percentiles, distributions, and clustering techniques such as K-means

  • Understanding of deep learning fundamentals, LLMs, and modern inference serving frameworks

Ways to stand out from the crowd:

  • Hands-on experience with traffic or network simulators, even in an academic or course project context

  • Familiarity with roofline modeling and performance scaling of deep learning models at the kernel level

  • Experience running large-scale simulation campaigns and building data pipelines to process and visualize results

  • Prior work characterizing or benchmarking ML inference workloads

NVIDIA is widely considered one of the technology world's most desirable employers. We work on problems that matter — and we do it with some of the most talented engineers on the planet. If you're analytically sharp, intellectually curious, and ready to have real impact, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 7, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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Aplyr's read

NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.

Synthesized from recent postings & public sources

What's promising

  • NVIDIA leads the GPU market, crucial for gaming and AI applications.
  • The company invests heavily in AI and deep learning, driving technological advancements.
  • NVIDIA's strong market position offers stability and growth opportunities for employees.

What to watch

  • High competition in the semiconductor industry can impact market share.
  • Rapid technological changes require constant adaptation and learning.
  • Intense workload and high expectations may affect work-life balance.

Why NVIDIA

  • NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
  • The company's AI research is at the forefront of deep learning innovation.
  • NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.

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About NVIDIA

NVDA$218.66+1.82%

NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.

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