Lead Machine Learning Engineer

Disney Entertainment & Sports LLC is seeking a Lead Machine Learning Engineer in San Francisco, CA (onsite) to help ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack. This role leads innovation for Disney’s personalization systems, covering ranking, modeling, candidate retrieval, post-ranking, experimentation, and production-ready ML engineering.

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 recommendation systems, including generating and improving recommendations, strengthening system evaluation, and accelerating how models are built and improved.
• Provide technical ideas and guidance on recommendation approaches and evaluation methodology, including how to define data, features, and objectives; support other scientists in shaping and productionizing their work.
• Drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and guiding how the team approaches them.
• Design and run rigorous offline and online experiments; contribute to improving evaluation systems and methodology.
• Collaborate within the team and across Engineering, Product, and Data partners by communicating methodologies clearly to technical and non-technical audiences and managing stakeholder expectations.
• Build production-worthy, maintainable systems that enable rapid iteration while maintaining strong standards for development, testing, and deployment, and respond to production issues as needed.

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 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.
• A collaborative, personable working style with success working within and across teams.

Technologies

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

Preferred Qualifications

• 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.

Education

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

Location and Compensation

Location: San Francisco, CA (onsite)

Salary: USD 187,900 - 252,000 per year