Senior Manager, Machine Learning Engineering

Adobe

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Work type
On-site
Location
San Jose, CA
Employment
Full-time
Posted
39 days ago
Freshness
Confirmed live today

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Similar $234k
$172k $302k
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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 282 open roles on FindRole.

Listed pay typically runs $148,100–$282,100 across 76 roles with salary data.

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TL;DR · Senior Manager, Machine Learning Engineering

The Sr Manager, Machine Learning Engineering joins the Applied Research team to serve as a technical and strategic steward for the Adobe Firefly Foundry platform. This role involves leading a distributed team focused on training data for generative AI, specifically managing the acquisition, processing, curation, and annotation of large-scale datasets. You will build and maintain scalable data pipelines, ensuring data diversity and bias mitigation while collaborating with researchers and ML engineers. Key technical requirements include expertise in ML data lifecycles for GANs and diffusion models, as well as proficiency with AWS, Azure, GCP, Spark, Databricks, and Snowflake. The work addresses the business problem of enabling enterprises to train private generative models on their own intellectual property while maintaining strict data isolation and copyright indemnification.

What you'll do

  • Lead and grow a distributed team focused on training data for Generative AI.
  • Define and execute strategies for acquiring, processing, curating, and annotating large-scale datasets.
  • Build and maintain scalable, efficient data pipelines across the entire training data lifecycle.
  • Champion data diversity, bias mitigation, and ethical AI practices.
  • Evaluate and integrate new tools and methodologies to enhance infrastructure and workflows.
  • Influence model development by providing insights on data quality and availability.

What we're looking for

  • Master’s/Ph.D. in CS, Data Science, Engineering, AI/ML, or related field, or equivalent experience.
  • 5+ years of experience in engineering leadership, managing data infrastructure or ML data ops teams.
  • 7+ years of experience building and optimizing large-scale ETL/ELT pipelines and data warehousing.
  • Deep understanding of ML data lifecycles, especially for generative models like GANs and diffusion.
  • Expertise in data quality, governance, versioning, and annotation platforms.
  • Proficiency with cloud data technologies including AWS, Azure, GCP, Spark, Databricks, and Snowflake.
  • Strong grasp of data privacy, security, and ethical AI principles.
  • Experience with large-scale image/video datasets (preferred).

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