Senior Research Scientist, Machine Learning Systems & Efficiency Engineer

Adobe

Quick summary

Work type
On-site
Location
Seattle, WASan Francisco, CASan Jose, CA
Salary
$187,100–$270,950 / yr
Posted
4 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $208k
This role $229k
$150k most similar roles pay here $284k

This role pays more than 69% of similar roles. Most pay $169,405–$246,150 — the shaded band above. At the midpoint, this role pays about $229k versus about $208k 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 301 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 299 roles with salary data.

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At a glance

TL;DR · Senior Research Scientist, Machine Learning Systems & Efficiency Engineer

Role Posting Log in to save

Photoshop ART seeks a Senior Machine Learning Systems & Efficiency Engineer to join its R&D team, focusing on delivering cost-effective and efficient inference systems for image editing applications. This role involves designing high-throughput, low-latency inference systems, optimizing model architectures using techniques like distillation and quantization, and implementing advanced serving strategies such as distributed inference and GPU kernel development with Triton or CUDA. The ideal candidate will have expertise in distributed inference, multimodal model profiling, and performance optimization, working closely with research and infrastructure teams to improve GPU utilization and build scalable ML systems. Proficiency in Python and C++, along with experience in tools like PyTorch Profiler and NVIDIA Nsight, is essential for this hands-on role that drives significant cost savings through efficient system design and deployment.

Skills

Python C++ CUDA Triton TensorRT ONNX Runtime PyTorch Profiler NVIDIA Nsight vLLM SGLang xDiT NCCL Kubernetes Docker Transformers Multimodal models 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 and define best practices.

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 or Triton for high-performance workloads.
  • Hands-on experience with open-source serving frameworks and inference tools.
  • Strong background in model architectures like Transformers and multimodal models.
  • Ability to conduct deep performance analysis using profiling tools.
  • Experience in designing scalable distributed serving systems across hardware.

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