Senior Deep Learning Computer Architect

About the role

NVIDIA is seeking architects to design hardware accelerator and processor architectures that enable state-of-the-art machine learning and data analytics algorithms and applications on their next-generation mobile, embedded, and datacenter platforms.

Responsibilities

• Contribute to features that advance the state of AI on next-generation GPUs.
• Collaborate with diverse teams, including DL researchers, hardware architects, and software engineers.
• Analyze the behavior of various deep learning methods.
• Propose new features to accelerate or enable various methods.
• Study the benefits of proposed features.

Requirements

• MS or PhD degree in computer science, computer architecture, electrical engineering or related field or equivalent experience.
• 5+ years of relevant experience in at least a few of the following areas: Computer architecture, including GPU and system level architecture; Performance analysis and optimization; Experience with LLM workloads, including performance tuning considerations such as parallelization and fusion strategies; Experience with core deep learning kernels such as matrix multiply, attention, and communication convolution; Programming fluency with C++ and ideally Python; Experience with GPU computing (CUDA); Experience with deep learning frameworks like PyTorch.

Qualifications

• Experience with intelligent machines powered by AI, including self-driving cars and robots learning motor skills.

Skills

• Knowledge of AI and machine learning technologies.
• Experience with deep learning frameworks and techniques.
• Ability to analyze and optimize complex systems.
• Strong problem-solving and analytical skills.

Benefits

• Equity and benefits package.

Pay

• Base salary range: $184,000 - $287,500 USD.

Schedule

• Full-time position.