Senior Deep Learning Performance Architect
Description For Senior Deep Learning Performance Architect
NVIDIA, the world leader in accelerated computing, is seeking a Senior Deep Learning Performance Architect to push the boundaries of AI and high-performance computing. This role sits at the intersection of hardware architecture and artificial intelligence, focusing on developing innovative solutions that will shape the future of GPU and deep learning technologies.
The position offers an exciting opportunity to work on cutting-edge technology that powers AI computers capable of learning, reasoning, and interacting with people. As part of NVIDIA's Deep Learning Architecture team, you'll be responsible for developing and analyzing next-generation architectures that accelerate AI applications, working with both single and multi-node configurations.
The role requires a strong technical background, with a minimum of 4 years of experience in parallel computing architectures and deep learning applications. You'll need expertise in Python and C++ programming, along with a deep understanding of GPU architecture and modern transformer-based model architectures. The position demands both technical depth and the ability to communicate complex concepts to diverse audiences.
Working at NVIDIA means being at the forefront of the AI revolution. The company is increasingly recognized as "the AI computing company" and plays a crucial role in developing technologies that power everything from robots to self-driving cars. The compensation package is competitive, with a base salary range of $184,000 to $287,500, plus equity and comprehensive benefits.
This role offers the unique opportunity to work with cutting-edge technology while contributing to innovations that are transforming multiple industries. You'll be part of a team that's driving real-time, cost-effective computing platforms in an exciting and rapidly growing field. The position is available in multiple locations including Santa Clara, Austin, and Hillsboro, offering flexibility in terms of location while maintaining the opportunity to work on groundbreaking technology.
Responsibilities For Senior Deep Learning Performance Architect
- Develop innovative HW architectures for parallel computing performance
- Benchmark and analyze AI workloads in single and multi-node configurations
- Develop high level simulator and analysis tools in C++/Python
- Evaluate PPA (performance, power, area) for hardware features
- Work closely with peer architecture teams and product management
- Keep abreast with emerging trends and research in deep learning
Requirements For Senior Deep Learning Performance Architect
- MS or PhD in Computer Science, Electrical Engineering, Computer Engineering, or equivalent experience
- 4+ years of experience in parallel computing architectures and deep learning applications
- Background in GPU or Deep Learning ASIC architecture evaluation
- Strong programming skills in Python and C++
- Solid fundamental knowledge in computer architecture and interconnect fabrics
- Understanding of modern transformer-based model architectures
- Ability to communicate technical concepts to non-technical audience
- Problem-solving skills and curious demeanor
Benefits For Senior Deep Learning Performance Architect
- Equity
- Benefits package available at nvidia.com/benefits
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