Senior Deep Learning Algorithm Engineer

Posted 7 Days Ago
Be an Early Applicant
2 Locations
Remote
184K-357K
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves researching, designing, and optimizing deep learning systems, particularly focusing on large language models and enhancing LLM inference efficiency.
Summary Generated by Built In

At NVIDIA, we are at the forefront of the constantly evolving field of large language models, and their application in agentic and reasoning use cases. As the scale and complexity of these LLM systems continues to increase, we are seeking outstanding engineers to join our team and help shape the future of LLM inference.

Our team is dedicated to pushing the boundaries of what's possible with LLMs by improving the algorithmic performance and efficiency of systems that represent them. We constantly reflect on how to improve these systems, developing new inference algorithms and protocols, improving existing models, and seamlessly integrating improvements to ensure NVIDIA's solutions can efficiently handle large-scale, sophisticated tasks.

What you'll be doing: 

  • Research and Development: Explore and incorporate contemporary research on generative AI, agents, and inference systems into the NVIDIA LLM software stack.

  • Workload Analysis and Optimization: Conduct in-depth analysis, profiling, and optimization of agentic LLM workloads to significantly reduce request latency and increase request throughput while maintaining workflow fidelity.

  • System Design and Implementation: Design and implement scalable systems to accelerate agentic workflows and efficiently handle sophisticated datacenter-scale use cases.

  • Collaboration and Communication: Advise future iterations of NVIDIA software, hardware, and system by engaging with a diverse set of teams at NVIDIA and external partners and formalizing the strategic requirements presented by their workloads.

What we need to see: 

  • BS, MS, PhD in Computer Science, Electrical Engineering, Computer Engineering, or a related field (or equivalent experience).

  • 8+ years of experience in deep learning and deep learning systems design.

  • Proficiency in Python and C++ programming

  • Strong understanding of computer architecture, and GPU/parallel datacenter computing fundamentals.

  • Proven interest in analyzing, modeling, and tuning application performance.

Ways to stand out from the crowd: 

  • Experience in building large-scale LLM inference systems, especially those involving compound AI.

  • Experience with processor and system-level performance modeling.

  • GPU programming experience with CUDA or OpenCL.

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.

The base salary range is 184,000 USD - 356,500 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.

Top Skills

C++
Cuda
Opencl
Python
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The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

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.”

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