Senior Machine Learning Engineer - News

Disney Disney · Media · New York, NY +2

Senior Machine Learning Engineer focused on building and operating ML systems for personalized news content delivery across various platforms. The role involves designing and developing infrastructure for the full ML lifecycle, including data pipelines, feature engineering, training, and low-latency online serving. Key responsibilities include driving ML-driven solutions for recommendation systems, RAG, and autogenerated tagging, and ensuring scalable, impactful solutions.

What you'd actually do

  1. Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence
  2. Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries
  3. Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs
  4. Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
  5. Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution

Skills

Required

  • 5+ years of experience building and operating ML engineering systems in production environments
  • Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
  • Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low-latency online serving
  • Experience designing and developing backend microservices for large-scale distributed systems using REST
  • Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
  • Familiarity with developing and deploying Spark and ML pipelines
  • Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
  • Experience with observability tools for metrics, logging, and monitoring such as Datadog

Nice to have

  • Bachelor’s degree in Computer Science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
  • Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
  • Experience working in Agile/Scrum development environments
  • Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment

What the JD emphasized

  • building and operating ML engineering systems in production environments
  • low-latency online serving
  • scalable learning, inference, and monitoring
  • real-time content personalization
  • low-latency personalized content delivery at scale

Other signals

  • personalized experiences
  • real-time content personalization
  • recommendation algorithms
  • ML infrastructure
  • low-latency personalized content delivery