Senior Software Engineer - Automated Parallel Programming

Posted 23 Days Ago
Be an Early Applicant
Santa Clara, CA
Senior level
Artificial Intelligence • Hardware • Robotics • Software • Metaverse
The Role
The Senior Software Engineer will develop tools for AI applications at scale, improving GPU performance using PyTorch and crafting a code generation system for deep learning models. The role involves collaboration with various engineering teams and influences hardware design at NVIDIA.
Summary Generated by Built In

The PyTorch Team @ NVIDIA is hiring passionate parallel programmers. Join us to design and build the tools used by millions of AI practitioners deploying AI applications scalable to thousands of GPUs. Our team is responsible for the continual delivery of best in class experience on NVIDIA's hardware with PyTorch. Join our team and collaborate with many multi-disciplinary engineering teams within NVIDIA and internationally in the PyTorch open source community to deliver our customers the best of NVIDIA software.

In this position you will learn innovative techniques from NVIDIA's domain experts for efficiently programming the world's most sophisticated computer systems. Build these techniques into NVIDIA/Fuser (commonly known as "nvFuser") applying our groundbreaking Parallel Programming Theory, allowing these optimization techniques to be applied to algorithms broadly, automatically, and safely to algorithms written in Numpy and PyTorch. Beyond building nvFuser influence and improve the entire software stack all the way from users to the CUDA compiler, to the Lightning-Thunder Graph Compiler, as well as influence the future design of NVIDIA's hardware platform. Join our ambitious and diverse team who strive to lead the best in AI programming.

What you will be doing:

  • Crafting a code generation system to accelerate portions of a graph collected from a machine learning framework.

  • Partnering with NVIDIA’s hardware and software teams to improve GPU performance in PyTorch.

  • Design, build and support production AI solutions used by enterprise customers and partners.

  • Optimize the performance of influential, modern Deep Learning models coming out of academic and industry research, for NVIDIA GPUs and systems.

  • Collaborating with internal applied researchers to improve their AI tools.

  • Advise design of new hardware generations.

What we need to see:

  • MS or PhD Computer Science, Computer Engineering, Electrical Engineering or a related field (or equivalent experience).

  • Parallel programming experience with writing optimized kernels in the NVIDIA CUDA Programming Language or similar parallel languages

  • 4+ years of experience with C++ programming.

  • Demonstrated experience developing large software projects.

  • We require excellent verbal and written communication skills.

Ways to stand out from the crowd:

  • Proven technical foundation in CPU and GPU architectures, numeric libraries, modular software design.

  • A background in deep learning compilers or compiler infrastructure

  • Expertise with optimized distributed parallelism techniques and it's a bonus if that includes parallelizing Large Language Models!

  • Knowledge of heuristic generation that employs cost models, machine learning, or auto-tuning.

  • Contributions to PyTorch, Numpy, JAX, TensorFlow, OpenAI-Triton, Lightning Thunder, TVM, Halide or similar system.

The base salary range is 180,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

Top Skills

C++
Cuda
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

Similar Jobs

Voltage Park Logo Voltage Park

Senior Full Stack Engineer

Artificial Intelligence • Cloud • Hardware • Machine Learning • Other • Software • Infrastructure as a Service (IaaS)
San Francisco, CA, USA
51 Employees
150K-200K Annually
Hybrid
San Francisco, CA, USA
289097 Employees
Hybrid
San Francisco, CA, USA
289097 Employees

General Motors Logo General Motors

JR-202424245 Manager, Software Engineer

Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
Hybrid
Mountain View, CA, USA
165000 Employees
182K-285K Annually

Similar Companies Hiring

Jobba Trade Technologies, Inc. Thumbnail
Software • Professional Services • Productivity • Information Technology • Cloud
Chicago, IL
45 Employees
RunPod Thumbnail
Software • Infrastructure as a Service (IaaS) • Cloud • Artificial Intelligence
Charlotte, North Carolina
53 Employees
Hedra Thumbnail
Software • News + Entertainment • Marketing Tech • Generative AI • Enterprise Web • Digital Media • Consumer Web
San Francisco, CA
14 Employees

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account