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Deep Learning Performance Architect at NVIDIA
Shanghai, Shanghai, China -
Full Time

Start Date

Immediate

Expiry Date

29 Aug, 26

Salary

0.0

Posted On

01 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Deep Learning, Computer Architecture, GPU Architecture, Performance Optimization, System Architecture Design, Machine Learning Frameworks, Performance Analysis, Hardware-Software Co-design

Industry

Computer Hardware Manufacturing

Description
NVIDIA is developing GPU and system architectures that accelerate deep learning, automotive and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to optimize deep learning hardware and software architecture and make a significant impact in a dynamic technology focused company What you’ll be doing: Analyze performance of various deep learning algorithms on different architectures Identify architecture and software performance bottlenecks and propose optimizations Explore new features and hardware capabilities on deep learning applications What we need to see: BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,) 5+ years of working experience in relevant directions will be a plus Be familiar with GPU or accelerator-based deep learning platform and software stack A strong background in computer architecture Experience on system architecture design and performance optimization Familiar with machine learning and deep learning frameworks NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry. Learn more about NVIDIA.
Responsibilities
Analyze the performance of deep learning algorithms across various architectures to identify bottlenecks. Propose optimizations and explore new hardware capabilities to improve deep learning software and hardware architecture.