Senior Deep Learning Engineer

About the Role

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 targeting frontier workloads including multi-agent AI systems, generative multimodal models, and inference-time compute scaling. In this role, you will characterize these emerging workloads and develop novel methods to optimize for them across inferencing engines, systems, and hardware architectures. Your work will span multiple tiers of the inference stack from the algorithmic to 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

• Continuously keeping up to date on the latest advancements in generative AI research.
• Analyzing and prototyping emerging workloads in multi-agent AI systems, generative multimodal models, and inference-time compute scaling.
• Pioneering and developing optimizations for these workloads across the inference stack to push the boundaries of inferencing quality and speed on NVIDIA systems.
• Collaborating closely with production teams to incorporate the latest advancements into cutting-edge software frameworks.

What We Need to See

• Master's 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.
• A track record of at least 5 years of relevant software development experience in modern deep learning frameworks such as PyTorch.
• Growth mindset and pragmatic attitude.

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, multimodal generation, AI systems, etc.
• Experience with prototyping or deployment of agentic AI systems and/or multimodal generation models.
• 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.