Senior Deep Learning Performance Architect

Posted 14 Days Ago
Be an Early Applicant
Santa Clara, CA, USA
In-Office
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design and prototype high-performance, energy-efficient processor and system architectures for deep learning. Develop analytical models, simulators, and test suites; profile and analyze performance and power trade-offs for DL workloads; collaborate with software, research, and product teams.
Summary Generated by Built In

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA is seeking extraordinary architects to develop processor and system architectures that accelerate machine learning, data analytics and high-performance computing applications. This position offers the chance to create a meaningful impact in a dynamic, technology-focused company.

What you will be doing:

  • As a member of our deep learning architecture team, you will craft high performance energy efficient system and processor architectures to extend the state of the art in deep learning.

  • Prototype key deep learning and data analytics algorithms and applications.

  • Analyze trade-offs in performance, cost and power developing analytical models, simulators and test suites.

  • Analyze architecture performance and/or energy efficiency considering deep learning workloads, modeling and prototyping.

  • Collaborate across the company to guide the direction of machine learning, working with software, research and product teams.

What we need to see:

  • Master's or PhD in Computer Science, Electrical Engineering or Computer Engineering, or equivalent experience.

  • 4+ years of relevant work or research experience.

  • A strong foundation in machine learning and deep learning fundamentals to complement your expertise in computer architecture.

  • A strong background in high performance power efficient designs, energy efficient high performance computing, performance analysis and profiling to identify performance bottlenecks.

  • Fluency in programming languages such as Python, C, C++.

  • Experience and familiarity with GPU computing and parallel programming models.

  • You have firsthand work experience with analytical performance modeling, profiling, and analysis.

The GPU started out as the engine for simulating human imagination, conjuring up the amazing virtual worlds of video games and Hollywood films. Now, NVIDIA’s GPU runs deep learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and artificial intelligence come together in our architecture. Today, NVIDIA GPUs are used broadly for deep learning, and NVIDIA is increasingly known as “the AI computing company.”

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 in the world working for us. Are you creative and seeking new challenges? If so, we want to hear from you! Come, join our DL Architecture team and help build the real-time, cost-effective AI computing platform driving our success in this exciting and quickly 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 28, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.

Skills Required

  • Master's or PhD in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience.
  • 4+ years of relevant work or research experience.
  • Strong foundation in machine learning and deep learning fundamentals.
  • Strong background in high-performance, power-efficient design, energy-efficient HPC, performance analysis and profiling.
  • Fluency in Python, C, C++.
  • Experience and familiarity with GPU computing and parallel programming models.
  • Hands-on experience with analytical performance modeling, profiling, and analysis.

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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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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