Lead Machine Learning Engineer

The Walt Disney Company

Lead Machine Learning Engineer developing personalization algorithms for Disney's media platforms. Ideating, iterating, and productionizing ML models across recommendation systems.

Posted 7/13/2026full-timeSan Francisco • California • 🇺🇸 United StatesSenior💰 $187,900 - $252,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and deploying machine learning models, particularly in recommendation systems, utilizing modern AI and LLM techniques. Strong ability to communicate complex methodologies to both technical and non-technical stakeholders while driving innovation in personalization algorithms.

Highest-signal resume keywords

Machine Learning Model DevelopmentRecommendation Systems ModelingAI and LLM TechniquesPyTorchTensorFlow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningApplied ML ScienceEnd-to-End ML EngineeringRecommendation SystemsData Features DefinitionEvaluation MethodologyMathematical Underpinnings of MLAlgorithm DevelopmentExperiment DesignModel Productionization

Soft Skills

Strong Communication SkillsCollaborative Working StylePersonable Interaction

Tools & Technologies

DatabricksSparkSQL

Industry Keywords

Personalization AlgorithmsTechnical VisionInnovation AgendaOffline and Online Experiments

Tech Stack

Tools & technologies

PyTorchSparkSQLTensorflow

About the role

Key responsibilities & impact

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.
Contribute ideas and insight on recommendation approaches, evaluation methodology, and how we define data, features, and objectives for our models.
Help drive the technical vision and innovation agenda for personalization.
Design and run rigorous offline and online experiments, and contribute to improving our evaluation systems and methodology.
Work closely within the team and across Engineering, Product, and Data partners, communicating methodologies clearly to technical and non-technical audiences.

Requirements

What you’ll need

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 ideally 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 rather than operating in isolation.

Benefits

Comp & perks

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/or other benefits, dependent on the level and position offered