Senior Deep Learning Performance Architect

at Nvidia

USD 184,000-356,500 per year

SENIOR

✅ On-site

Tech Stack
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1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 4 Deep Learning @ 7 GPU @ 7 HPC JAX LLM @ 3 Machine Learning @ 6 Performance Analysis @ 4 Profiling @ 4 PyTorch Python @ 7 TensorRT

Details

We are now seeking a Senior Deep Learning Performance Architect. NVIDIA is looking for outstanding Performance Architects with a background in performance analysis, performance modeling, and AI/deep learning to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications.

Responsibilities

Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs. Develop high level simulators in C++/Python
Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

Requirements

MS or PhD in Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
6+ years of relevant meaningful work experience
Strong background in GPU or Deep Learning ASIC architecture for distributed training and/or inference spanning multi-chip/multi-node
Experience with performance modeling, architecture simulation, profiling, and analysis
Solid foundation in machine learning and deep learning. Understanding of modern transformer-based architectures and their performance at scale.
Strong programming skills in Python, C, C++

Ways to stand out from the crowd

Background with deep neural network training, inference and optimization in leading frameworks (e.g. Pytorch, JAX, TensorRT)
Familiarity with advanced optimizations and SW/HW co-design in LLM training and inference
Exposure to using AI to accelerate SW engineering
Demonstration of self-motivation and creative / critical thinking

NVIDIA describes this as part of its Deep Learning Architecture team, helping build real-time, efficient computing platforms for its success in this 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.