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Manager, Machine Learning Engineering

Manager, Machine Learning Engineering

Adobe Inc.San Jose, CA, United States
1 day ago
Job type
  • Full-time
Job description

Overview

Our Company

Changing the world through digital experiences is what Adobe's all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences. We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.

We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

The Opportunity

AdobeFireflyFoundry is a managed generative-AI service purpose-built for enterprises that need to scale content creation without compromising brand safety or workflow efficiency. By letting customers train private Firefly models on their own intellectual property—under strict data isolation and copyright indemnification—and deploy those models directly into Adobe Creative Cloud, Experience Cloud, and proprietary platforms via FireflyServices APIs, Foundry closes the gap left by consumer-grade GenAI tools and empowers brands to deliver ten times the creative output at professional quality.

As a Manager for Applied Research at Adobe, you will be the technical and strategic steward of this platform, translating state-of-the-art research into secure, production-ready capabilities, championing them in customer and industry settings, and building the world-class team that will turn vision into reality.

Responsibilities

  • Lead and grow a distributed team focused on training data for Generative AI.
  • Define and execute strategy for acquiring, processing, curating, annotating, versioning, and ensuring quality of large-scale datasets for Adobe Firefly.
  • Build and maintain scalable, efficient data pipelines across the training data lifecycle.
  • Collaborate with researchers, ML engineers, and PMs to align on data needs for new models.
  • Champion data diversity, bias mitigation, and ethical AI practices.
  • Evaluate and integrate tools and methodologies to enhance infrastructure and workflows.
  • Influence model development through insights on data quality and availability.
  • Provide technical leadership and foster a culture of innovation.
  • Partner across teams to align data priorities and share best practices.

Qualifications

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

  • Familiarity with MLOps tools (e.g., DVC), annotation platforms, and compliance standards.
  • Experience in computer vision, multimedia, or creative content data ecosystems.
  • Contributions to open-source tools, publications, or patents in data management.
  • Proven success supporting generative model training with robust data solutions.
  • Compensation

    Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $168,200 – $340,100 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

    At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

    In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

    State-Specific Notices

    California : Fair Chance Ordinances – Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and fair chance ordinances.

    Colorado : Application Window Notice – If this role is open to hiring in Colorado, the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.

    Massachusetts : Massachusetts Legal Notice – It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

    Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

    If you require accommodations to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

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    Engineering Manager Machine Learning • San Jose, CA, United States

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