Senior Deep Learning Performance Architect, Compute Energy Efficiency

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

NVIDIA is seeking outstanding Performance Architects with a background in performance and energy efficiency of parallel architectures, performance modeling, architecture simulation, and workload profiling to help analyze and develop the next generation of architectures at scale, to 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

• Prototype key deep learning algorithms and applications

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

• Characterize performance and energy efficiency on scale out systems and work with architecture and systems team to identify and evaluate features to increase at scale efficiency of systems running AI workloads.

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

• Actively collaborate with software, systems and research teams to guide the direction of deep learning hardware and software

What we need to see:

• A Masters Degree (or equivalent experience) and 5+ years of meaningful relevant experience or PhD and 2+ years of experience in Computer Science, Electrical Engineering, Computer Engineering, or related field

• Good foundation in Deep Learning model architectures and performance tradeoffs

• Experience with energy efficient high performance analysis, architecture/system co-design and/or simulation, profiling, and visualizations

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

• Experience with the parallel computing architectures, or workload analysis on Deep Learning accelerators

Ways to stand out from the crowd:

• Background with GPU Computing and parallel programming models such as CUDA

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

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.”

Widely considered to be one of the technology world’s most desirable employers, NVIDIA has some of the most forward-thinking and hardworking people in the world inventing the future for us. Are you a creative and collaborative software engineer seeking new challenges? If so, we want to hear from you! Come, join us 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 184,000 USD - 287,500 USD.Applications for this job will be accepted at least until August 19, 2025.

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.