Manager, Machine Learning Engineering - Ad Platforms

Disney Disney · Media · Seattle, WA +2

Manager, Machine Learning Engineering for Ad Platforms at Disney. This role involves leading a team of Data Scientists and ML Engineers to build, enhance, and maintain high-performance, distributed, microservice-based advertising platforms. Responsibilities include mentoring, driving best practices, defining strategic direction, overseeing end-to-end ML workflows (data collection, model development, deployment), fostering innovation, and ensuring responsible AI practices. Requires experience in translating business problems into scalable ML/GenAI solutions, deploying ML systems in production using cloud platforms and MLOps, and proficiency in Python and ML/DL frameworks.

What you'd actually do

  1. Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection.
  2. Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms.
  3. Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders.
  4. Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards.
  5. Develop partnerships across the organization to identify and prioritize high-impact ML opportunities.

Skills

Required

  • people management
  • technical leadership
  • machine learning fundamentals
  • deep learning
  • statistical modeling
  • designing, building, and deploying scalable machine learning models and systems in production
  • deploying ML/GenAI systems at scale using cloud platforms and MLOps practices
  • Python
  • TensorFlow
  • PyTorch

Nice to have

  • Java

What the JD emphasized

  • scalable ML and GenAI solutions
  • deploying scalable machine learning models and systems in production
  • deploying ML/GenAI systems at scale using cloud platforms and MLOps practices

Other signals

  • ad serving
  • machine learning engineering
  • people management
  • production deployment
  • MLOps