Lead Machine Learning Engineer

Disney Entertainment and ESPN Product & Technology is seeking a Lead Machine Learning Engineer to help shape and deliver personalization capabilities for Disney+ and Hulu. In this onsite role in San Francisco, CA, you will ideate, develop, iterate on, and productionize machine learning models and ranking systems across the recommendation stack, using modern AI and LLM techniques and rigorous evaluation to improve the recommendations users see.

What you will do

• Ideate, develop, iterate on, and productionize personalization algorithms spanning core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
• Apply modern AI and LLM techniques to recommendation systems, including generating and improving recommendations, strengthening evaluation, and accelerating how models are built and improved.
• Contribute ideas and insight across recommendation approaches and evaluation methodology, including how data, features, and objectives are defined for modeling and how those ideas are shaped into production systems.
• Help drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and setting the team’s approach.
• Design and run rigorous offline and online experiments, and contribute to improving evaluation systems and methodology.
• Collaborate within the team and across Engineering, Product, and Data partners, communicating methodologies clearly to technical and non-technical audiences and managing stakeholder expectations.
• Build production-worthy, maintainable systems with strong standards for development, testing, and deployment, and step in to support production issue resolution when needed.

Required qualifications

• 7+ years of experience developing machine learning models and deploying them to production systems.
• Strong background in applied ML science, end-to-end ML engineering, or a blend, with experience in recommendation systems modeling.
• Hands-on experience with AI and LLM techniques and an understanding of the modern AI landscape.
• Proficiency with tools and frameworks including PyTorch, TensorFlow, Databricks, Spark, and SQL.
• In-depth understanding of modern machine learning methods, models, and their mathematical foundations.
• Strong written and verbal communication skills.
• Collaborative, personable working style and ability to work well across teams.

Education

• BS or MS in Computer Science, Engineering, or a related field.

Technologies

• PyTorch, TensorFlow, Databricks, Spark, SQL, AI, LLM

Compensation and benefits

The salary range for this role is USD 187,900 - 252,000 per year. A bonus and/or long-term incentive units may be provided as part of the compensation package, along with a full range of medical, financial, and/or other benefits depending on the level and position offered.

Preferred qualifications

• PhD in computer science, statistics, math, or a related quantitative field.
• Publications or papers in machine learning or AI, particularly in recommender systems.
• Production experience developing content recommendation algorithms at scale.
• Experience with reinforcement learning or related sequential decision-making approaches.
• Experience with evaluation methodology for recommendation systems, including offline evaluation and A/B experimentation.