Lead Machine Learning Engineer

The Walt Disney Company; San Francisco (CA); On-site; USD 187,900 - 252,000; Full time

Job summary

The Walt Disney Company is seeking a Lead Machine Learning Engineer to ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack for Disney+ and Hulu.

You will work with the Core ML team, building real‑time ranking, content understanding models, and collaborating with engineers, product, and data partners to run experiments and maintain scalable systems.

Qualifications

• 7+ years of experience building ML models and deploying to production.
• Experience in applied ML science and end-to-end ML engineering with recommender systems.
• Hands-on experience with AI and LLM techniques.
• Strong written and verbal communication skills.

Responsibilities

• Ideate, develop, and productionize personalization algorithms across the recommendation stack.
• Apply AI/LLM techniques to improve recommendations and evaluation.
• Design experiments and maintain scalable production‑ready systems.
• Collaborate across Engineering, Product, and Data teams.

Skills

Machine learning development

End-to-end ML engineering

Recommendation systems

PyTorch

TensorFlow

Databricks

Spark

SQL

Communication

Team collaboration

Education

BS/MS in Computer Science or related field

Tools

Databricks

Spark

SQL

Job description

Lead Machine Learning Engineer

Job Summary: We are looking for a Lead Machine Learning Engineer to help ideate, develop, iterate on, and productionize personalization algorithms across the recommendation stack for Disney+ and Hulu. The role blends applied science and engineering, driving the vision and innovation behind Disney’s personalization systems to delight users through great content recommendations.

As part of the Core ML team, you will work at the intersection of research and production, building real‑time ranking, content and user understanding models, candidate retrieval, and post‑ranking systems. You will collaborate with engineers, product, and data partners to design experiments, refine evaluation methods, and maintain scalable, maintainable production‑ready systems.

Responsibilities

• Algorithm development: Ideate, develop, iterate on, and productionize personalization algorithms, including core ranking, content and user understanding models and graphs, candidate retrieval, and post‑ranking systems.
• AI and LLM innovation: Apply modern AI and LLM techniques to recommendation systems, using them to generate and improve recommendations, strengthen system evaluation, and accelerate model development.
• Applied science: Contribute ideas and insight on recommendation approaches, evaluation methodology, and data, feature, and objective definition for models, and help other scientists bring their ideas to production.
• Vision and roadmap: Drive the technical vision and innovation agenda for personalization, identifying high‑impact opportunities and shaping team strategy.
• Experimentation and evaluation: Design and run rigorous offline and online experiments, and improve evaluation systems and methodology.
• Collaboration: Work closely across Engineering, Product, and Data partners, communicating methodologies clearly to technical and non‑technical audiences and managing stakeholder expectations.
• ML engineering: Build production‑worthy, maintainable systems that are easy to iterate on, uphold strong standards for development, testing, and deployment, and support production issues as needed.

Basic 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 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.
• A collaborative, personable working style; works well within the team and across teams.

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.

Required Education

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

The hiring range for this position in San Francisco, CA is $187,900.00 – $252,000.00 per year. The base pay actually offered will consider internal equity and may vary based on the candidate’s geographic region, job‑related knowledge, skills, and experience. A bonus and/or long‑term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and other benefits.

About Disney Entertainment and ESPN Product & Technology

Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business worldwide. The team marries technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses.

Equal Employment Opportunity

Disney Entertainment & Sports LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, religion, color, sex, sexual orientation, gender, gender identity, gender expression, national origin, ancestry, age, marital status, military or veteran status, medical condition, genetic information, or disability, or any other basis prohibited by federal, state or local law. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.