Senior Staff Machine Learning Engineer

Adobe

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Seattle, WASan Jose, CA
Salary: $190,200–$345,650 / yr
Employment: Full-time
Posted: 12 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $234k

This role $268k

$165k $365k

below market most similar roles pay here above market

This role pays more than 85% of similar roles. Most pay $213,235–$254,750 — the blue band above. At the midpoint, this role pays about $268k versus about $234k 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 282 open roles on FindRole.

Listed pay typically runs $148,100–$282,100 across 76 roles with salary data.

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At a glance

TL;DR · Senior Staff Machine Learning Engineer

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The Sr Staff Machine Learning Engineer joins the Generative AI Services team to build scalable, high-performance generative AI systems for products like Firefly, Photoshop, and Illustrator. This role involves designing and developing efficient inference pipelines, optimizing models for latency and throughput, and building APIs to integrate first-party and third-party generative models into the Adobe suite. You will build ML workflows for enterprise-scale model customization, serve models, and optimize GPU-accelerated pipelines for training and inference. Key technical requirements include proficiency with PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python. You must understand generative model architectures such as diffusion models, transformers, and GANs. The work focuses on the productization of research models, solving complex engineering challenges in model serving, orchestration, and GPU resource management within distributed systems.

What does a Machine Learning Engineer earn in Washington?

Median $241750 from 69 postings across 15 companies.

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Skills

Python PyTorch CUDA Triton TensorRT Nvidia Dynamo Kubernetes MLOps Distributed Systems Diffusion Models Transformers GANs Model Serving Inference Pipelines

What you'll do

Design and develop core GenAI services and APIs to integrate generative models into flagship products.
Build ML workflows for enterprise-scale model customization, serving, and ecosystem integration.
Optimize GPU-accelerated pipelines for model training and inference to ensure performance and scalability.
Develop efficient inference pipelines to minimize latency and maximize throughput for generative AI systems.
Partner with research teams to productize model inference strategies and integrate first-party and third-party models.
Set technical direction and mentor other machine learning engineers on complex engineering challenges.
Manage GPU resources and orchestration in large-scale production environments using Kubernetes and MLOps platforms.

What we're looking for

MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent industry experience.
10+ years of experience in machine learning, including production-scale deployments.
3+ years of experience leading large-scale, GPU-intensive GenAI systems for training, inference, and optimization.
Experience with GenAI frameworks and tools such as PyTorch, CUDA, Triton, TensorRT, Nvidia Dynamo, and Python.
Good understanding of generative model architectures, including diffusion models, transformers, and GANs.
Good communication and leadership skills with a track record of driving alignment in matrixed organizations.
Experience with model serving, inference, orchestration, and GPU resource management in large-scale environments (preferred).
Hands-on expertise in Kubernetes, distributed systems, and MLOps platforms (preferred).