Lead Machine Learning Engineer

The Walt Disney Company • Santa Monica, CA

2d • $187,900 - $252,000

About The Position

Disney Entertainment and ESPN Product & Technology builds and advances the technological foundation for Disney’s media business. Within Product Engineering, the Core ML team owns the core personalization algorithms powering Disney+ and Hulu, spanning real-time ranking, content and user understanding, candidate retrieval, and post-ranking for a large streaming audience.

The Lead Machine Learning Engineer will ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack. The role combines applied science and machine learning engineering, with opportunities to contribute to recommendation approaches and evaluation methodology, bring ideas into production at scale, and help maintain systems that are reliable and easy to iterate on. The position will help shape the technical vision and innovation agenda for personalization, with an emphasis on using modern AI and LLM techniques to improve recommendations and the processes used to build and evaluate them. The goal is to improve the personalization experience, customer satisfaction, and understanding of content and users.

Requirements

• 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 of both, with experience in recommendation systems modeling.
• Hands-on experience with AI and LLM techniques and a solid understanding of the modern AI landscape.
• Proficiency with tools and frameworks such as PyTorch, TensorFlow, Databricks, Spark, and SQL.
• In-depth understanding of modern machine learning methods, models, and their mathematical underpinnings.
• Strong written and verbal communication skills.
• Collaborative, personable working style and ability to work across teams.
• BS or MS in Computer Science, Engineering, or a related field.

Nice To Haves

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

Responsibilities

• Ideate, develop, iterate on, and productionize personalization algorithms, including core ranking, content and user understanding models and graphs, candidate retrieval, and post-ranking systems.
• Apply modern AI and LLM techniques to generate and improve recommendations, strengthen evaluation, and accelerate model development and improvement.
• Contribute ideas on recommendation approaches, evaluation methodology, and the data, features, and objectives used in models; help other scientists shape and productionize their ideas.
• Help drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and shaping the team’s approach.
• Design and run rigorous offline and online experiments, and contribute to improving evaluation systems and methodology.
• Collaborate with Engineering, Product, and Data partners; communicate methodologies to technical and non-technical audiences and manage stakeholder expectations.
• Build production-worthy, maintainable systems that are easy to iterate on, uphold strong development, testing, and deployment standards, and support production issue response.

Benefits

• Medical benefits.
• Financial benefits.
• Other benefits, depending on the level and position offered.
• A bonus and/or long-term incentive units may be provided as part of the compensation package.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior