[Remote] Senior Deep Learning Performance Architect
Note: The job is a remote job and is open to candidates in USA. NVIDIA is seeking a Senior Deep Learning Performance Architect to analyze and develop next-generation architectures that accelerate AI and high-performance computing applications. The role involves developing innovative hardware architectures, benchmarking AI workloads, and collaborating with architecture teams to guide product development.
Responsibilities
- Develop innovative HW architectures to extend the state of the art in parallel computing performance, energy efficiency and programmability
- 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 and system-level architectural trade-offs
- Work closely with peer architecture teams and product management to guide development of the products
- Keep abreast with emerging trends and research in deep learning
Skills
- MS or PhD in a relevant discipline (Computer Science, Electrical Engineering, Computer Engineering, etc) or equivalent experience
- 4+ years of experience in parallel computing architectures, interconnect fabrics and deep learning applications
- Background in GPU or Deep Learning ASIC architecture evaluation for training and/or inference
- 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 simplify and communicate rich technical concepts to non-technical audience
- Have a curious demeanor with excellent problem-solving skills
Benefits
- You will also be eligible for equity and benefits.
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