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:
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Keeping abreast of the latest advancements in generative AI research.
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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.
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Pioneering the development of innovative optimizations to enable high quality inferencing on Nvidia GPUs.
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Collaborating closely with production teams to incorporate the latest advancements into cutting-edge software frameworks.
What We Need to See:
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Master's or PhD degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.
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A strong foundation in deep learning, with a particular emphasis on generative models and inferencing.
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Experience in modern deep learning frameworks such as PyTorch.
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Experience with benchmarking accuracy and performance of AI models.
Ways to Stand Out From the Crowd:
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Published research or noteworthy contributions to the field of deep learning, particularly in areas such as inference-time compute, conditional compute, speculative decoding, etc.
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Background with prototyping and/or deployment of emergent test time compute techniques.
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Experience with collaborating across algorithms, software and performance teams to deliver high quality solutions.
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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.
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What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
