Machine Learning Engineer, Firefly Services

Adobe

Quick summary

Work type
On-site
Location
SeattleSan Jose, CA
Salary
$161,700–$234,150 / yr
Posted
46 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $221k
This role $198k
$149k most similar roles pay here $278k

This role pays less than 70% of similar roles. Most pay $192,700–$249,750 — the shaded band above. At the midpoint, this role pays about $198k versus about $221k for comparable roles.

Based on 240 similar postings.

Employer

About Adobe

Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software

Adobe currently has 307 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 307 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Firefly Services

Adobe Firefly’s Generative AI Services team is seeking a Senior Machine Learning Engineer to lead the design and development of core generative AI services and APIs, integrating advanced models into Adobe’s flagship products. This role involves collaborating with Adobe Research and other model developer teams to optimize GPU-accelerated pipelines for both training and inference, ensuring high performance, scalability, and reliability in large-scale environments. Ideal candidates will have a strong background in machine learning, including experience with frameworks like PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python, as well as expertise in generative model architectures such as diffusion models, transformers, and GANs. Additionally, hands-on knowledge of Kubernetes, distributed systems, and MLOps platforms is preferred for managing GPU resources effectively in complex, matrixed organizations.

What you'll do

  • Design and develop core generative AI services and APIs for Adobe’s products.
  • Build GPU-accelerated pipelines for model training and inference, focusing on performance.
  • Optimize large-scale, GPU-intensive systems for generative AI training and inference.
  • Collaborate with research teams to productize generative models using advanced frameworks.
  • Mentor other machine learning engineers and set technical direction within the team.

What we're looking for

  • MS or PhD in Computer Science, Machine Learning, or related field.
  • 1-3+ years of experience in machine learning with production-scale deployments.
  • Experience leading large-scale GPU-intensive generative AI systems.
  • Proficiency in PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python.
  • Expertise in diffusion models, transformers, GANs, and model serving frameworks.
  • Strong communication and leadership skills for matrixed organizations.
  • Hands-on experience with Kubernetes, distributed systems, and MLOps platforms.

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