Senior Deep Learning Performance Architect, Compute Energy Efficiency
Job Description
NVIDIA is seeking an exceptional Senior Deep Learning Performance Architect to join their team focusing on Compute Energy Efficiency. This role sits at the intersection of deep learning, high-performance computing, and energy efficiency optimization. As a world leader in accelerated computing, NVIDIA offers an opportunity to work on cutting-edge technology that's transforming industries through AI and digital twins.
The position involves developing next-generation architectures that push the boundaries of deep learning performance and efficiency. You'll be working with state-of-the-art GPU technology, developing and optimizing deep learning algorithms, and conducting sophisticated performance analysis. The role requires a unique blend of deep learning expertise, architecture knowledge, and performance optimization skills.
This is an ideal opportunity for someone with strong technical capabilities in parallel computing, deep learning, and system architecture who wants to impact the future of AI computing. You'll be working with NVIDIA's industry-leading GPU technology and collaborating with top talent across software, systems, and research teams. The company offers competitive compensation, including equity, and the chance to work on technology that's driving innovation across multiple industries.
The position is based in Santa Clara, CA, offering the chance to work at the heart of Silicon Valley's tech ecosystem. NVIDIA's commitment to innovation, coupled with their position as "the AI computing company," makes this an exciting opportunity for someone looking to make a significant impact in the field of deep learning and energy-efficient computing.
Responsibilities For Senior Deep Learning Performance Architect, Compute Energy Efficiency
- 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
- Understand and analyze the interplay of hardware and software architectures
- Collaborate with software, systems and research teams
Requirements For Senior Deep Learning Performance Architect, Compute Energy Efficiency
- Masters Degree (or equivalent experience) and 5+ years of meaningful relevant experience or PhD and 2+ years of experience
- Good foundation in Deep Learning model architectures and performance tradeoffs
- Experience with energy efficient high performance analysis, architecture/system co-design
- Strong programming skills in Python, C, C++
- Experience with parallel computing architectures or workload analysis on Deep Learning accelerators
Benefits For Senior Deep Learning Performance Architect, Compute Energy Efficiency
- Equity
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