Sr. Machine Learning Engineer, Adobe Firefly Services

Adobe

Seattle, United States
Base: $151,800 -- $265,350 annually; bonus/equity:...
Generative ai systems
Inference pipelines
Model optimization
Design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe’s first-party and third-party generative models into Adobe suite of products

Job Summary

  • Design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe’s first-party and third-party generative models into Adobe suite of products.
  • Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration, collaborating with Adobe Research and other model developer teams with a focus on model inference strategies and productization.
  • Build and optimize GPU-accelerated pipelines for both (customized) model training and inference—prioritizing performance, scalability, and reliability.

Matching Summary

Design and develop efficient inference pipelines, optimize models for latency and through at inference, and build APIs and ecosystems that integrate both Adobe’s first-party and third-party generative models into Adobe suite of products.

Salary

Base: $151,800 -- $265,350 annually; Bonus/Equity: Not specified; Benefits: Not specified

Skills & Requirements

Must-have

  • Generative AI systems
  • Inference pipelines
  • Model optimization
  • GPU-accelerated pipelines
  • PyTorch, CUDA, Triton, TensorRT
  • Generative model architectures

Nice-to-have

  • Culture of innovation
  • Technical excellence
  • Continuous improvement
  • Driving alignment in matrixed organizations

Key Requirements

  • MS or PhD in Computer Science, Machine Learning, or related field or equivalent industry experience
  • 7+ years of experience in machine learning
  • 3+ years of experience leading large-scale, GPU-intensive GenAI systems
  • Experience with GenAI frameworks and tools
  • Good understanding of generative model architectures
  • Good communication and leadership skills

Work Rights

Not specified

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