Senior Deep Learning Performance Architect

at Nvidia

📍 Santa Clara, United States

USD 184,000-287,500 per year

SENIOR

✅ On-site

Tech Stack
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AI Deep Learning @ 6 GPU @ 4 HPC Python @ 7

Details

NVIDIA is seeking a Senior Deep Learning Performance Architect to analyze and develop next-generation architectures that accelerate artificial intelligence and high-performance computing applications.

Responsibilities

Develop innovative hardware architectures that advance parallel computing performance, energy efficiency, and programmability.
Benchmark and analyze AI workloads in single-node and multi-node configurations.
Develop high-level simulation and analysis tools using C++ and Python.
Evaluate performance, power, and area (PPA) for hardware features and system-level architectural trade-offs.
Collaborate with peer architecture teams and product management to guide product development.
Stay current with emerging trends and research in deep learning.

Requirements

Master's or PhD degree in a relevant discipline, such as Computer Science, Electrical Engineering, or Computer Engineering, or equivalent experience.
At least 4 years of experience with parallel computing architectures, interconnect fabrics, and deep learning applications.
Experience evaluating GPU or deep learning ASIC architectures for training and/or inference.
Strong programming skills in Python and C++.

Preferred Qualifications

Strong fundamental knowledge of computer architecture and interconnect fabrics.
Understanding of modern transformer-based model architectures.
Ability to simplify and communicate complex technical concepts to non-technical audiences.
Curiosity and excellent problem-solving skills.

Benefits

The base salary range is USD 184,000–287,500 per year, determined by location, experience, and compensation for employees in similar positions. The role also includes eligibility for equity and benefits.