Machine Learning Engineer, Adobe Firefly Services

ADOBE

Multiple Locations
Base: $151,800 -- $265,350 annually; bonus/equity:...
Design and develop efficient inference pipelines
Optimize models for latency and throughput
Build scalable, high-performance generative ai systems
You will 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 that serve individual and enterprise customers

Job Summary

  • You will 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 that serve individual and enterprise customers.
  • Design and evelopment of core GenAI services and APIs that integrate a wide range of generative models into Adobe’s flagship products.
  • Build and optimize GPU-accelerated pipelines for both (customized) model training and inference—prioritizing performance, scalability, and reliability.

Matching Summary

You will 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 that serve individual and enterprise customers.

Salary

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

Skills & Requirements

Must-have

  • design and develop efficient inference pipelines
  • optimize models for latency and throughput
  • build scalable, high-performance generative AI systems
  • GenAI frameworks and tools (PyTorch, CUDA, Triton, TensorRT)
  • generative model architectures (diffusion, transformers, GANs)

Nice-to-have

  • foster a culture of innovation
  • technical excellence and continuous improvement
  • driving alignment in matrixed organizations

Key Requirements

  • MS or PhD or equivalent industry experience
  • 4-7+ years in machine learning production deployments
  • 2+ years leading large-scale GPU-intensive GenAI systems
  • Experience with Python

Work Rights

Not specified

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