Sr Manager, Machine Learning Engineering, Firefly Services

Adobe Adobe · Enterprise · San Jose, CA

Senior Manager, Machine Learning Engineering for Adobe Firefly's GenAI Product Services team. The role involves leading a team to build, deploy, optimize, and scale generative models and APIs for enterprise customers. Responsibilities include technical leadership, strategy definition, roadmap shaping, and cross-functional collaboration. The ideal candidate has strong experience in generative AI, production-scale ML deployments, and engineering leadership.

What you'd actually do

  1. Tech lead projects that delivers critical ML services and APIs to integrate first- and third-party models and pipelines for Enterprise customers
  2. Collaborate cross-functionally with PMs, PMMs, TPMs, and other engineering teams to shape the roadmap of Adobe’s Enteprise Gen AI space
  3. Act as a technical leader and coach, guiding a team of ML and platform engineers through complex, high-stakes projects.
  4. Explore and research new and emerging ML and MLOps technologies to continuously improve Adobe’s GenAI engineering effectiveness and efficiency
  5. Review and provide feedback on features, technology, architecture, designs, test strategies, and service reliability standards.

Skills

Required

  • MS/PhD in Computer Science, AI/ML, or related fields, or equivalent industry experience.
  • 8+ years of experience in machine learning, including production-scale deployments.
  • 5+ years of engineering leadership experience, with a track record of growing and mentoring high-performing teams.
  • Strong background in generative AI technologies (e.g., GANs, diffusion models, transformers).
  • Proven ability to lead large, cross-functional teams through complex, time-sensitive projects.
  • Excellent communication skills, with a knack for influence and driving alignment in matrix organizations.

Nice to have

  • Hands-on experience with training, fine-tuning, inference, and optimization of generative models, multi-modality models.
  • Hands-on familiarity with optimizing and converting models across formats

What the JD emphasized

  • production-scale deployments
  • engineering leadership experience
  • track record of growing and mentoring high-performing teams
  • Proven ability to lead large, cross-functional teams through complex, time-sensitive projects.

Other signals

  • leading a team of ML and service engineers
  • designing, deploying, optimizing and scaling generative models and APIs
  • define long-term strategy, shape the technical roadmap
  • enterprise genAI space