NVIDIA Logo

NVIDIA

AI and ML Infra Software Engineer, GPU Clusters - New College Grad 2026

Posted 4 Days Ago
In-Office
Santa Clara, CA, USA
124K-242K Annually
Entry level
In-Office
Santa Clara, CA, USA
124K-242K Annually
Entry level
Design, implement, and optimize GPU-cluster AI/ML infrastructure to boost researcher productivity: identify infrastructure gaps, monitor and tune performance, define efficiency metrics, and collaborate with research, data engineering, and DevOps teams to enable scalable distributed training and inference workflows.
The summary above was generated by AI

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re 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 a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

We are currently hiring an AI/ML Infrastructure Software Engineer at NVIDIA to join our Hardware Infrastructure team. As an Engineer, you will play a crucial role in boosting productivity for our researchers through implementing advancements across the entire stack. Your primary responsibility will involve working closely with customers to identify and resolve infrastructure gaps, enabling innovative AI and ML research on GPU Clusters. Together, we can create powerful, efficient, and scalable solutions as we shape the future of AI/ML technology!

What you will be doing:

  • Collaborate closely with our AI and ML research teams to understand their infrastructure needs and obstacles, translating those observations into actionable improvements.

  • Monitor and optimize the performance of our infrastructure ensuring high availability, scalability, and efficient resource utilization.

  • Help define and improve important measures of AI researcher efficiency, ensuring that our actions are in line with measurable results.

  • Collaborate with diverse teams, including researchers, data engineers, and DevOps professionals, to build a seamless and coordinated AI/ML infrastructure ecosystem.

  • Stay on top of the latest advancements in AI/ML technologies, frameworks, and effective strategies, and promote their implementation within the company.

What we need to see:

  • Recent graduate with a MS, PhD or equivalent experience in Computer Science or related field, with proven experience in AI/ML and HPC workloads and infrastructure.

  • Hands-on experience in using or operating High Performance Computing (HPC) grade infrastructure as well as in-depth knowledge of accelerated computing (e.g., GPU, custom silicon), storage (e.g., Lustre, GPFS, BeeGFS), scheduling & orchestration (e.g., Slurm, Kubernetes, LSF), high-speed networking (e.g., Infiniband, RoCE, Amazon EFA), and containers technologies (Docker, Enroot).

  • Expertise in running and optimizing large-scale distributed training workloads using PyTorch (DDP, FSDP), NeMo, or JAX. Also, possess a deep understanding of AI/ML workflows, encompassing data processing, model training, and inference pipelines.

  • Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.

  • Passion for continual learning and keeping abreast of new technologies and effective approaches in the AI/ML infrastructure field.

  • Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds.

NVIDIA provides competitive salaries and a comprehensive benefits package. Our engineering teams are expanding rapidly due to exceptional growth. If you're a passionate and independent engineer with a love for technology, 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 July 27, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

An Hour Ago
Remote or Hybrid
USA
124K-207K Annually
Senior level
124K-207K Annually
Senior level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Lead optimization and experimentation for Pfizer's HCP web properties (primarily PfizerPro). Develop experimentation roadmaps, run A/B and multivariate tests, analyze web and business metrics, partner with UX, analytics, and strategy to translate insights into product and design improvements, and adopt AI-enabled tools to scale personalization and accelerate test velocity while maintaining rigorous measurement.
Top Skills: A/B TestingAdobe AnalyticsAdobe TargetAi-Enabled Optimization And Personalization ToolsClaude DesignContent Management SystemsFigma MakeMultivariate TestingOptimizelyVwoWeb Analytics
An Hour Ago
In-Office
215K-358K Annually
Senior level
215K-358K Annually
Senior level
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Lead identification, evaluation, and acquisition of external drug candidates and technologies to accelerate preclinical and early clinical development. Advise senior leaders, lead cross-functional scientific diligence, assess emerging computational and AI platforms, drive portfolio strategy and competitive intelligence, and foster collaboration across P&TS and Discovery Network to advance research priorities.
Top Skills: ChatgptComputational TechnologiesGenerative AiMicrosoft Copilot
An Hour Ago
Hybrid
274K-457K Annually
Expert/Leader
274K-457K Annually
Expert/Leader
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Lead cross-platform product and adoption for three strategic AI platforms and an AI marketplace. Own end-to-end colleague experience, adoption model, federated champions network, design research, catalog curation, and adoption/value measurement. Influence engineering roadmaps, report realized value, and grow a small senior core to drive governed-path adoption and measurable enterprise outcomes.
Top Skills: ClaudeCopilotForge49GeminiLoomMemxSnowflakeTableau

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account