Senior AI Training Performance Architect
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Role details
Tech stack
Job description
We are now looking for a Senior AI Training Performance Architect
Requirements
Artificial Intelligence (AI), Artificial Intelligence (AI), Computer Systems, Construction, Performance Analysis, GPU (Graphics Processing Unit), Performance Tuning/Optimization, Analysis Skills, Deep Learning, Workload Automation, * PhD in CS, EE or CSEE (or equivalent experience) with 5+ years of relevant experience; or MS with 8+ years of experience.
- Strong background in deep learning and neural networks, particularly in training.
- Solid understanding of computer architecture and familiarity with GPU architecture fundamentals.
- Proven background in analyzing and tuning application performance.
- Proven experience with processor and system-level performance modeling.
- Proficiency in programming with C++, Python, and CUDA.
Benefits & conditions
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.
About the company
NVIDIA is seeking a senior engineer who is obsessed with performance analysis and optimization to help us squeeze every last clock cycle out of AI training, the workload driving the design and construction of the largest and most powerful compute systems in the world. If you are willing to work across all layers of the hardware/software stack - from GPU architecture to the application code - to achieve peak performance, we want to hear from you. This role offers the opportunity to directly impact the hardware and software roadmap in a fast-growing technology company that leads the AI revolution. Join us and help design and build the worldβs most powerful compute systems!
What you will be doing:
- Understand, analyze, profile, and optimize AI training workloads on state-of-the-art hardware and software platforms.
- Identifying performance bottlenecks of AI training on GPUs, prioritizing and then solving problems across the key AI training workloads.
- Implement production-quality software across multiple layers of NVIDIAβs deep learning platform stack, from drivers to DL frameworks.
- Build and support NVIDIA submissions for MLPerf Training benchmarks.
- Implement key DL training workloads in NVIDIAβs proprietary processor and system simulators to enable future architecture studies.
- Develop tools to automate workload analysis, optimization, and other critical workflows., NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. Itβs a unique legacy of innovation thatβs fueled by great technology-and amazing people. Today, weβre tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing whatβs never been done before takes vision, innovation, and the worldβs best talent. As an NVIDIAN, youβll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
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