Fall 2025

Applied AI Research Engineering Intern

Posted on 7/1/2025

Deadline 7/7/25
NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$18 - $71/hr

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

In Person

Category
AI & Machine Learning (2)
,
Required Skills
Kubernetes
Rust
Python
Git
Data Structures & Algorithms
Go
REST APIs
Requirements
  • Pursuing Bachelors or Masters in Computer Science or a related field
  • Excellent Golang, Rust and/or Python programming and software design skills, including debugging, performance and service health analysis, and test design
  • Good understanding of algorithms and data structures, solid knowledge of RESTful APIs
  • Highly motivated, dedicated, and curious about new technologies
  • Excellent communication, planning, and problem solving skills.
Responsibilities
  • Collaborate on the design and development of the Dynamo Kubernetes stack.
  • Introduce new features to the Dynamo Python SDK and Dynamo Rust Runtime Core Library; design, implement, and optimize distributed inference components in Rust and Python.
  • Contribute to the development of disaggregated serving for Dynamo-supported inference engines (vLLM, SGLang, TRT-LLM, llama.cpp, mistral.rs).
  • Improve intelligent routing and KV-cache management subsystems.
  • Contribute to open-source repositories, participate in code reviews, assist with issue triage on GitHub, work closely with the community to address issues, capture feedback, and evolve the framework’s APIs and architecture.
Desired Qualifications
  • Understanding of machine learning or NLP concepts
  • Experience in software shipping cycles (dev, deploy, release, CI) and open-source software development
  • Experience working with inference engines such as vLLM, SGLang TensorRT-LLM and similar
  • Experience building and deploying containers in Kubernetes environments

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

Simplify Jobs

Simplify's Take

What believers are saying

  • Agentic AI spending is accelerating, lifting data center revenue and inference demand.
  • Hyperscaler capex remains massive, with NVIDIA positioned at the center of buildouts.
  • Photonic and edge computing investments open adjacent infrastructure markets beyond traditional chips.

What critics are saying

  • AMD, Alphabet, and custom silicon pressure NVIDIA pricing and share in AI accelerators.
  • TSMC dependence exposes NVIDIA to Taiwan disruptions, export controls, and capacity bottlenecks.
  • China export restrictions permanently shrink a major end market and encourage domestic rivals.

What makes NVIDIA unique

  • CUDA and full-stack software create sticky developer lock-in around NVIDIA GPUs.
  • Blackwell GPUs dominate AI training and inference workloads across hyperscale data centers.
  • Vera CPUs extend NVIDIA beyond GPUs into a new $200 billion market.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-1%
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