NVIDIA Logo

NVIDIA

Senior Deep Learning Performance Architect

Posted 19 Hours Ago
Be an Early Applicant
2 Locations
Senior level
2 Locations
Senior level
The Senior Deep Learning Performance Architect at NVIDIA will develop advanced architectures to enhance deep learning performance, analyze performance trade-offs, and collaborate with various teams to guide deep learning hardware and software direction. The role requires a strong understanding of deep learning frameworks, performance modeling, and programming skills in Python and C/C++.
The summary above was generated by AI

We are now seeking a Senior Deep Learning Performance Architect!

NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning 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 architectures to extend the state of the art in deep learning performance and efficiency

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

  • Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications

  • Develop, analyze, and harness groundbreaking Deep Learning frameworks, libraries, and compilers

  • Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

What we need to see:

  • MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience

  • 6+ years of meaningful work experience

  • Strong background in GPU or Deep Learning ASIC architecture for training and/or inference

  • Experience with performance modeling, architecture simulation, profiling, and analysis

  • Solid foundation in machine learning and deep learning

  • Strong programming skills in Python, C, C++

Ways to stand out from the crowd:

  • Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)

  • Experience with relevant libraries, compilers, and languages - CUDNN, CUBLAS, CUTLASS, MLIR, Triton, CUDA, OpenCL

  • Experience with the architecture of or workload analysis on other DL accelerators

  • Demonstration of self-motivation, with a knack for critical thinking and thinking outside the box

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, efficient computing platforms driving our success in this exciting and rapidly growing field.

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.

HQ

NVIDIA Seattle, Washington, USA Office

4545 Roosevelt Way NE 6th Floor, Seattle, Washington, United States, 98105

Similar Jobs

6 Hours Ago
4 Locations
Senior level
Senior level
Cloud • Information Technology • Machine Learning
The Senior Software Engineer will design, develop, and maintain networking software for GPU cloud services, optimizing performance, security, and scalability while collaborating with cross-functional teams. Responsibilities include troubleshooting, staying updated on networking technologies, and participating in code reviews and architecture decisions.
6 Hours Ago
4 Locations
Junior
Junior
Cloud • Information Technology • Machine Learning
The Engineer for Fleet Monitoring & Analysis will design and implement solutions to enhance observability of a global hardware fleet, maintain metrics, alerts, and visualizations, and support automated provisioning and management efforts while contributing to on-call duties.
8 Hours Ago
Remote
Hybrid
Seattle, WA, USA
95K-168K Annually
Senior level
95K-168K Annually
Senior level
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
The Senior Systems Engineer will lead the development and adoption of procurement solutions, optimize procurement efficiency, and manage integrations with systems like Coupa and Oracle ERP. This role calls for deep technical expertise and leadership to drive transformation in procurement technology and operations.

What you need to know about the Seattle Tech Scene

Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.

Key Facts About Seattle Tech

  • Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Amazon, Microsoft, Meta, Google
  • Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
  • Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Madrona, Fuse, Tola, Maveron
  • Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account