Senior Deep Learning Performance Architect - LPU

NVIDIA Corporation; Texas; Sur place; USD 152 000 - 241 500; Plein temps

Résumé du poste

NVIDIA is seeking a Senior Deep Learning Performance Architect in Wisconsin to push the boundaries of AI Inference performance. You will design advanced GPU architectures and collaborate across teams to enhance AI strategies. Candidates should have a strong mathematical foundation in machine learning and expert programming skills in C, C++, and/or Python.

The role offers a competitive salary range of $152,000 to $241,500 based on experience.

Qualifications

• 5+ years of relevant experience.
• Strong knowledge of GPU computing.
• Experience in performance modeling.

Responsabilités

• Design GPU architectures to enhance AI Inference performance.
• Collaborate across teams to guide AI direction.
• Build efficient AI inference models.

Connaissances

Programming in C, C++, and/or Python

Mathematics in machine learning and deep learning

GPU computing (CUDA or similar)

HPC (MPI, OpenMP) stack

Computer architecture

Formation

MS or PhD in CS, EE, Math or equivalent experience

Description du poste

Overview

We are now looking for a Senior Deep Learning Performance Architect! NVIDIA seeks a Senior DL Performance Architect to join our group of pioneers who enjoy pushing AI Inference performance boundaries. Our team focuses on ambitious hardware-software co-design to speed AI Inference workloads. This role gives an outstanding opportunity to develop world-class performance strategies, guide future GPU architecture decisions, and lead AI innovation. If you are passionate about AI efficiency Pareto curves, have a proven record of modeling LLM performance and architecting AI systems, and enjoy optimizing every cycle, this role may be perfect for you!

What You\'ll Be Doing

• Design novel GPU and system architectures to advance the forefront of AI Inference performance and efficiency
• Construct, investigate, and test popular deep learning algorithms and applications
• Understand and analyze the relationship between hardware and software architectures as it influences future algorithms and applications
• Build efficient power and performance models of AI inference stack, while capturing minimal but significant information to guide next-gen HW architecture
• Collaborate across the company to guide the direction of AI, working with software, research, and product teams

What We Need To See

• A MS or PhD in a relevant field (CS, EE, Math) or equivalent experience, with 5+ years of relevant experience
• Strong mathematical foundation in machine learning and deep learning
• Expert programming skills in C, C++, and/or Python
• Familiarity with GPU computing (CUDA or similar) and HPC (MPI, OpenMP) stack
• Strong knowledge and coursework in computer architecture

Ways To Stand Out From The Crowd

• Background with systems-level performance modeling, profiling, and analysis
• Experience in characterizing and modeling system-level performance, accomplishing comparison studies, and documenting and publishing results
• Background in improving AI Inference workloads by developing CUDA kernels or compilers for custom ASIC hardware

Base salary and benefits details are subject to location and experience. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive work environment and is an equal opportunity employer. We value diversity in our current and future employees and do not discriminate on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.