Senior AI Performance and Efficiency Engineer

NVIDIA; California (MO); On-site; USD 152,000 - 288,000; Full time

Benefits offered by this job

Equity

Competitive benefits

Job summary

NVIDIA is seeking a Senior AI/ML Performance and Efficiency Engineer for GPU Clusters to advance AI efficiency across researchers. You will collaborate with researchers to pinpoint infrastructure gaps, build tools, and deliver scalable solutions enhancing AI/ML workloads on GPU clusters.

The role requires strong ML technique knowledge, 5+ years in large-scale compute infra, and experience with distributed training and debugging tools. Equity and competitive benefits are provided.

Qualifications

• BS or similar background in Computer Science or related area (or equivalent experience).
• Minimum 5+ years of experience designing and operating large scale compute infrastructure.
• Strong understanding of modern ML techniques and tools.
• Experience investigating, and resolving, training & inference performance end to end.
• Debugging and optimization experience with NSight Systems and NSight Compute.
• Experience with debugging large-scale distributed training using NCCL.
• Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) and parallel computing frameworks.
• Dedication to ongoing learning and staying updated on new technologies in AI/ML infrastructure.
• Excellent communication and collaboration skills.

Responsibilities

• Collaborate closely with AI/ML researchers to improve model efficiency and productivity.
• Build tools and frameworks to detect efficiency bottlenecks and deliver improvements.
• Work on diverse ML workloads across Robotics, AV, LLMs, Videos, and more.
• Collaborate across engineering to optimize hardware, software, and infrastructure usage.
• Monitor fleet-wide utilization patterns and implement scalable solutions.
• Stay up-to-date with AI/ML tech and advocate to integrate them within the org.

Skills

Python

Go

Bash

CUDA

NVIDIA NCCL

NSight

Education

BS in Computer Science or related field

Tools

NSight Systems

NSight Compute

NCCL

PyTorch

TensorFlow

Lustre/GPFS

InfiniBand (IBOP/RDMA)

AWS/GCP/Azure

Job description

We are seeking a Senior AI/ML Performance and Efficiency Engineer, GPU Clusters at NVIDIA to join our AI Efficiency efforts. As an Engineer, you will have a pivotal role in enhancing efficiency for our researchers by implementing progressions throughout the entire stack. Your main task will revolve around collaborating closely with customers to pinpoint and address infrastructure and application deficiencies, facilitating groundbreaking AI and ML research on GPU Clusters. Together, we can craft potent, effective, and scalable solutions as we mold the future of AI/ML technology!

What You Will Be Doing

• Collaborate closely with our AI/ML researchers to make their ML models more efficient leading to significant productivity improvements and cost savings
• Build tools, frameworks, and apply ML techniques to detect & analyze efficiency bottlenecks and deliver productivity improvements for our researchers
• Work with researchers working on a variety of innovative ML workloads across Robotics, Autonomous vehicles, LLM's, Videos and more
• Collaborate across the engineering organizations to deliver efficiency in our usage of hardware, software, and infrastructure
• Proactively monitor fleet wide utilization patterns, analyze existing inefficiency patterns, or discover new patterns, and deliver scalable solutions to solve them
• Keep up to date with the most recent developments in AI/ML technologies, frameworks, and successful strategies, and advocate for their integration within the organization.

What We Need To See

• BS or similar background in Computer Science or related area (or equivalent experience)
• Minimum 5+ years of experience designing and operating large scale compute infrastructure
• Strong understanding of modern ML techniques and tools
• Experience investigating, and resolving, training & inference performance end to end
• Debugging and optimization experience with NSight Systems and NSight Compute
• Experience with debugging large-scale distributed training using NCCL
• Proficiency in programming & scripting languages such as Python, Go, Bash, as well as familiarity with cloud computing platforms (e.g., AWS, GCP, Azure) in addition to experience with parallel computing frameworks and paradigms.
• Dedication to ongoing learning and staying updated on new technologies and innovative methods in the AI/ML infrastructure sector.
• Excellent communication and collaboration skills, with the ability to work effectively with teams and individuals of different backgrounds

Ways To Stand Out From The Crowd

• Background with NVIDIA GPUs, CUDA Programming, NCCL and MLPerf benchmarking
• Experience with Machine Learning and Deep Learning concepts, algorithms and models
• Familiarity with InfiniBand with IBOP and RDMA
• Understanding of fast, distributed storage systems like Lustre and GPFS for AI/HPC workloads
• Familiarity with deep learning frameworks like PyTorch and TensorFlow

NVIDIA offers competitive salaries and a comprehensive benefits package. Our engineering teams are growing rapidly due to outstanding expansion.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. 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 a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) 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.