Used Tools & Technologies
Not specified
Required Skills & Competences ?
Python @ 6 Hiring @ 4 CUDA @ 6 GPU @ 4Details
NVIDIA has transformed computer graphics, PC gaming, and accelerated computing for over 25 years and is now focusing on AI to define the next era of computing. The role involves being part of a diverse, supportive environment, contributing to innovation, and making a lasting impact.
Responsibilities
- Understand, analyze, profile, and optimize AI training workloads on new hardware and software platforms, identifying fundamental performance limiters.
- Prioritize and solve performance issues across new neural networks, with attention to training performance on GPUs.
- Implement production-quality software across multiple layers of NVIDIA’s deep learning platform stack, from drivers to DL frameworks.
- Build and support NVIDIA submissions for MLPerf Training benchmarks.
- Implement key deep learning training workloads in proprietary processor and system simulators for future architecture studies.
- Develop tools to automate workload analysis, optimization, and other critical workflows.
Requirements
- PhD in Computer Science, Electrical Engineering, or Computer Science and Electrical Engineering (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 training.
- Solid understanding of computer architecture and GPU fundamentals.
- Proven experience analyzing and tuning application performance.
- Proven experience with processor and system-level performance modeling.
- Proficiency in C++, Python, and CUDA programming.
Benefits
NVIDIA offers highly competitive salaries, a comprehensive benefits package, and equity eligibility. They are committed to diversity and equal opportunity hiring practices. More details at www.nvidiabenefits.com.