Lead Machine Learning Engineer

Join Disney Entertainment & Sports LLC in San Francisco, CA (onsite) as a Lead Machine Learning Engineer. In this role, you will ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack. You will help shape the technical direction for Disney’s personalization systems, from ranking and modeling to candidate retrieval, experimentation, and production-ready machine learning engineering.

Compensation: USD 187,900 - 252,000 per year. Minimum experience: 7 years. Education: BS or MS in Computer Science, Engineering, or a related field.

What you’ll work on

• 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 model development and iteration.
• Provide insight on recommendation approaches, evaluation methodology, and how to define data, features, and objectives for models, helping other scientists translate ideas into production.
• Drive the technical vision and innovation agenda for personalization by identifying high-impact opportunities and shaping how the team tackles them.
• Design and run rigorous offline and online experiments, while contributing to improvements in evaluation systems and methodology.
• Partner across Engineering, Product, and Data to communicate methodologies clearly to technical and non-technical audiences and manage stakeholder expectations.
• Build production-worthy, maintainable systems that support iteration, with strong standards for development, testing, and deployment, and provide support when production issues arise.

What you bring

• 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, with an 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 comfort working across teams rather than operating in isolation.

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 evaluation methodology for recommendation systems, including offline evaluation and A/B experimentation.

Education

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

Technologies

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