Machine Learning Engineer, Adobe Firefly Services

Adobe Media and Data Science Research (MDSR) Laboratory

Base: $151,800 - $265,350 annually (us); californi...
Senior machine learning engineer role
4-7+ years ml production experience
2+ years gpu-intensive genai systems
This high-impact role involves building scalable, high-performance generative AI systems that power features across Adobe's flagship products like Firefly and Photoshop

Job Summary

  • This high-impact role involves building scalable, high-performance generative AI systems that power features across Adobe's flagship products like Firefly and Photoshop.
  • Candidates will design efficient inference pipelines, optimize models for latency and throughput, and integrate both first-party and third-party generative models into the Adobe suite.
  • The position requires mentoring other ML engineers, setting technical direction, and tackling complex engineering challenges at the forefront of the industry.

Matching Summary

This high-impact role involves building scalable, high-performance generative AI systems that power features across Adobe's flagship products like Firefly and Photoshop.

Salary

Base: $151,800 - $265,350 annually (US); California: $183,300 - $265,350; Washington: $165,600 - $239,725

Skills & Requirements

Must-have

  • Senior Machine Learning Engineer role
  • 4-7+ years ML production experience
  • 2+ years GPU-intensive GenAI systems
  • PyTorch CUDA Triton TensorRT expertise
  • Diffusion models transformers GANs knowledge

Nice-to-have

  • Leadership in matrixed organizations
  • Kubernetes distributed systems MLOps
  • Culture of innovation and excellence
  • Experience with Nvidia Dynamo
  • Model serving orchestration skills

Key Requirements

  • MS or PhD in Computer Science or related field
  • 4-7+ years of machine learning experience
  • 2+ years leading large-scale GPU-intensive GenAI systems
  • Strong communication and leadership skills
  • Track record of driving alignment in matrixed organizations

Work Rights

Not specified

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