Lead Machine Learning Engineer – News

The Walt Disney Company

Lead Machine Learning Engineer developing infrastructure for personalized content delivery at Disney. Collaborating across teams to drive machine learning innovation and support strategic initiatives.

Posted 6/24/2026full-timeGlendale • California, New York • 🇺🇸 United StatesSenior💰 $141,900 - $199,400 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsKafkaMicroservicesSpark

About the role

Key responsibilities & impact

Own complex technical initiatives end-to-end, from technical design through production deployment and operational excellence
Design and develop infrastructure supporting the full cycle of machine learning, including data pipelines and workflow orchestration, data discovery and quality tools, and feature libraries
Drive data and ML-driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging solutions, RAGs
Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
Strategically prioritize initiatives and technical workstreams to deliver the highest-impact and most time-sensitive outcomes, while proactively identifying, communicating, and mitigating risks to ensure successful execution
Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
Mentor and coach engineers, fostering a culture of ownership, collaboration, and continuous improvement
Contribute to technical documentation and promote knowledge sharing across teams

Requirements

What you’ll need

Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
7+ years of software engineering experience
5+ years of hands-on experience developing and deploying machine learning systems in production
Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
Comfortable operating at all levels of the predictive stack, including data collection, data analysis, feature engineering, batch training and low-latency online serving
Experience designing and developing backend microservices for large-scale distributed systems using REST
Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
Familiarity with developing and deploying Spark and ML pipelines
Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
Proven leadership, coaching, and mentoring skills, with the ability to inspire and empower a team towards achieving business goals
Experience with observability tools for metrics, logging, and monitoring such as Datadog
Experience working in Agile/Scrum development environments
Excellent communication skills and a commitment to collaboration in a fast-paced, guest-focused environment.

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.

ATS Keywords

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Hard Skills & Tools

machine learningdata pipelinesworkflow orchestrationfeature engineeringbackend microservicesRESTdeep learning algorithmsbig data technologiesSparkcloud infrastructure

Soft Skills

leadershipcoachingmentoringcollaborationcommunicationrisk managementstrategic prioritizationproblem-solvingcontinuous improvementownership