Sr Machine Learning Engineer- Ml Infrastructure & Data Platforms

ADOBE

Base: $172,500 - $306,625 annually (varies by loca...
8+ years building distributed systems
Python programming skills
Pytorch or tensorflow experience
This role involves building the infrastructure that powers large-scale, multimodal AI training and inference across billions of data points

Job Summary

  • This role involves building the infrastructure that powers large-scale, multimodal AI training and inference across billions of data points.
  • Candidates will develop distributed data loaders, batch inference systems, and vector-based retrieval systems to support high-volume GPU environments.
  • Adobe empowers employees to innovate with AI and seeks individuals who can turn model requirements into scalable, reliable systems.

Matching Summary

This role involves building the infrastructure that powers large-scale, multimodal AI training and inference across billions of data points.

Salary

Base: $172,500 - $306,625 annually (varies by location); California: $211,800 - $306,625; Washington: $201,000 - $291,150

Skills & Requirements

Must-have

  • 8+ years building distributed systems
  • Python programming skills
  • PyTorch or TensorFlow experience
  • Distributed computing tools like Ray or Spark
  • Cloud platform experience AWS or Azure
  • MLOps CI/CD workflow knowledge

Nice-to-have

  • Multimodal data experience images video text
  • Vector database familiarity
  • Semantic search system knowledge
  • Collaborative team environment participation

Key Requirements

  • Master's degree or Ph.D. in Computer Science or related field
  • Equivalent practical experience to Master's degree
  • 8+ years of production experience in ML infrastructure

Work Rights

Not specified

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