Senior Applied Scientist - Machine Learning Systems Engineer- Photoshop

Adobe

Quick summary

Work type
On-site
Location
Seattle · San Jose, CA
Salary
$216,400–$313,300 / yr
Posted
53 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $210k
This role $265k
$147k most similar roles pay here $331k

This role pays more than 87% of similar roles. Most pay $173,625–$246,325 — the shaded band above. At the midpoint, this role pays about $265k versus about $210k for comparable roles.

Based on 239 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 177 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 177 roles with salary data.

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At a glance

TL;DR · Senior Applied Scientist - Machine Learning Systems Engineer- Photoshop

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Photoshop ART seeks a Senior Machine Learning Systems & Efficiency Engineer to join its R&D team, focusing on enhancing inference performance and cost efficiency in image editing applications. This role involves designing high-throughput, low-latency systems using techniques like distillation, pruning, and quantization, while optimizing GPU utilization through kernel development and system acceleration. The ideal candidate will have expertise in distributed inference, multimodal model profiling, and performance optimization, with hands-on experience in frameworks such as Triton or CUDA. Proficiency in Python and C++, along with a strong understanding of GPU architecture and performance analysis tools like PyTorch Profiler and NVIDIA Nsight, is essential. The role requires collaboration with research and infrastructure teams to build scalable, cost-aware ML systems deployed across diverse hardware environments, aiming for substantial savings in compute costs.

Skills

Python C++ CUDA Triton TensorRT ONNX Runtime PyTorch Profiler NVIDIA Nsight Docker Kubernetes vLLM SGLang xDiT NCCL AllReduce AllGather Transformers Mixture-of-Experts Diffusion Transformers

What you'll do

  • Design and optimize high-throughput, low-latency inference systems.
  • Write and maintain high-performance GPU kernels to accelerate custom model layers.
  • Conduct deep performance analysis using profiling tools to identify system bottlenecks.
  • Partner with infrastructure teams to design scalable distributed serving systems.
  • Establish efficiency metrics and build benchmarking frameworks for cost-aware ML.
  • Serve as a technical advisor on efficiency tradeoffs in research and product teams.

What we're looking for

  • Deep expertise in machine learning systems and distributed inference.
  • Experience with GPU architecture and performance optimization techniques.
  • Proficiency in Python, C++, CUDA, and Triton for high-performance computing.
  • Hands-on experience with open-source serving frameworks and inference compilation tools.
  • Strong background in system-level performance analysis and profiling.
  • Technical leadership skills to define best practices for cost-efficient ML development.

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