Senior Deep Learning Performance Architect job opportunity at NVIDIA.

Home Jobs In United States Of America Tag: Job Senior Deep Learning Performance Architect position at NVIDIA


DateMore Than 30 Days Ago bot
NVIDIA Senior Deep Learning Performance Architect
Experience: 6-years
Pattern: full-time
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degreePhD
loacation US, CA, Santa Clara, United States Of America
loacation US, CA, Santa ..........United States Of America

We are now looking for a Senior Deep Learning Performance Architect!  NVIDIA is seeking outstanding Performance Analysis Architects with a background in performance and energy modeling, architecture simulation, and profiling 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 Prototype key deep learning algorithms and applications Analyze performance, cost and energy trade-offs by developing analytical models, simulators and test suites Characterize power and performance on silicon parts and translate the learnings to architecture features and simulators Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW What we need to see: A Masters Degree (or equivalent experience) and 6+ years of meaningful relevant experience or PhD and 3+ years of experience in Computer Science, Electrical Engineering, Computer Engineering, or related field Strong foundation in Deep Learning model architectures and workload analysis with emphasis on LLM decode architectures and performance tradeoffs Experience with performance and energy modeling, power architecture, architecture simulation, profiling, analysis, and visualizations Strong programming skills in Python, C++ 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) Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU-accelerated 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”, and widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package.   Are you a creative, motivated deep learning architect with a passion for performance and always up for a challenge? If so, we want to hear from 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 for Level 4, and 224,000 USD - 356,500 USD for Level 5. 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.

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