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NVIDIA

Deep Learning Engineer - New College Grad 2025

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At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking senior deep learning engineer to contribute to the development of next-generation inference optimizations and deliver industry-leading performance without compromising model quality. In this role, you will analyze and explore techniques to scale test-time compute and optimize low-latency inference. Your work will leverage cross-stack optimizations at the algorithmic and system level.

As NVIDIA makes significant strides in AI datacenters, our team holds a central role in maximizing the efficiency of our exponentially growing inference deployment needs and establishing a data-driven approach to algorithmic improvements, hardware design and system software development. We collaborate extensively with diverse teams at Nvidia, spanning deep learning research and framework development teams, to silicon architecture. Thriving in such a high-impact, interdisciplinary environment necessitates not only technical proficiency but also a growth mindset and a pragmatic attitude — qualities that fuel our collective success in shaping the future of datacenter technology.

What You'll Be Doing:

  • Keeping abreast of the latest advancements in generative AI research.

  • Prototyping and analyzing emergent techniques in the test-time compute space such as output refinement, speculation, and retrieval. Identifying opportunities for algorithmic as well as system optimizations.

  • Pioneering the development of innovative optimizations to enable high quality inferencing on Nvidia GPUs.

  • Collaborating closely with production teams to incorporate the latest advancements into cutting-edge software frameworks.

What We Need to See:

  • Master's or PhD degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.

  • A strong foundation in deep learning, with a particular emphasis on generative models and inferencing.

  • Experience in modern deep learning frameworks such as PyTorch.

  • Experience with benchmarking accuracy and performance of AI models.

Ways to Stand Out From the Crowd:

  • Published research or noteworthy contributions to the field of deep learning, particularly in areas such as inference-time compute, conditional compute, speculative decoding, etc.

  • Background with prototyping and/or deployment of emergent test time compute techniques.

  • Experience with collaborating across algorithms, software and performance teams to deliver high quality solutions.

  • Familiarity with computer architecture and how it relates to AI algorithms development.

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

The base salary range is 120,000 USD - 235,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse 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 Seattle, Washington, USA Office

4545 Roosevelt Way NE 6th Floor, Seattle, Washington, United States, 98105

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
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