Senior GPU Optimization Engineer

3 weeks ago

San Jose, United States Adobe Full time

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours

The Opportunity
Firefly is the new family of creative generative AI models coming to Adobe products that offers a new way to conceptualize, build, and scale content. It’s a natural extension of the technology Adobe has produced over the past 40 years.

At the core of Firefly are our commercially safe AI models trained on hundreds of millions of images owned or licensed by Adobe. We are hiring for a highly strategic and visible role to apply GPU optimization skills towards improving the training efficiency and performance of these models. This is an opportunity to reach millions of creatives, helping them reinvent the way they work.

What you will be working on:

  • Interfacing with model architecture teams to co-design with hardware in mind
  • Write efficient kernels for forward and backward passes in CUDA, Cutlass / CuTe, Triton
  • Write optimized custom layers using PyTorch
  • Leverage FP8 to accelerate training and inference
  • Optimize model efficiency for Hopper/Blackwell GPU architectures
  • Write high quality, product level code that is easy to maintain and test while following standard development methodologies

What you will need to succeed:

  • B.S., M.S, or Ph.D. in Computer Science, Computer Engineering or a related area and 5+ years related experience
  • Proficiency in Linux, Docker
  • Understanding of modern transformer-based model architectures
  • Expert in Python and PyTorch
  • Understanding of distributed training fundamentals
  • Experience in C++ with an emphasis on Python integration
  • Expert in CUDA, Triton
  • Experience with Cutlass / CuTe
  • Expert in profiling – Nsight, Kineto, etc.
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