Senior Deep Learning Performance Architect

Reposted 12 Hours Ago
Be an Early Applicant
3 Locations
In-Office
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The role involves developing innovative hardware architectures for AI, benchmarking AI workloads, and analyzing performance using C++ and Python.
Summary Generated by Built In

We are now looking for a Senior Deep Learning Performance Architect! 

NVIDIA is seeking outstanding Performance Analysis Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

What you'll be doing:

  • Develop innovative HW architectures to extend the state of the art in parallel computing performance, energy efficiency and programmability.

  • Benchmark and analyze AI workloads in single and multi-node configurations.

  • Develop high level simulator and analysis tools in C++/Python.

  • Evaluate PPA (performance, power, area) for hardware features and system-level architectural trade-offs.

  • Work closely with peer architecture teams and product management to guide development of the products.

  • Keep abreast with emerging trends and research in deep learning.

What we need to see:

  • MS or PhD in a relevant discipline (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience.

  • 4+ years of experience in parallel computing architectures, interconnect fabrics and deep learning applications.

  • Background in GPU or Deep Learning ASIC architecture evaluation for training and/or inference.

  • Strong programming skills in Python and C++. 

Ways to stand out from the crowd: 

  • Solid fundamental knowledge in computer architecture and interconnect fabrics.

  • Understanding of modern transformer-based model architectures.

  • Ability to simplify and communicate rich technical concepts to non-technical audience.

  • Have a curious demeanor with excellent problem-solving skills.

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. NVIDIA's GPUs run AI algorithms, simulating human intelligence, and act as the brains of computers, robots and self-driving cars that can perceive and understand the world. Increasingly known as “the AI computing company”, NVIDIA wants you. Come, join our Deep Learning Architecture team, where you can help build real-time, cost-effective computing platforms driving our success in this exciting and rapidly growing field!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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++
Python
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The Company
HQ: Santa Clara, CA
21,960 Employees
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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