Principal Machine Learning Engineer

Disney Entertainment & Sports LLC is looking for a Principal Machine Learning Engineer to shape the technical architecture and strategic direction of the News & Entertainment (N&E) ML platform across Disney’s portfolio of brands. This onsite role in Glendale, CA partners ML engineering leadership with a reliability-first mindset, aiming to improve personalization, recommendation quality, and end-to-end ML execution across a large, time-sensitive problem space.

Salary: USD 210,500 - 295,900 per year.

Experience: 10+ years in production ML engineering systems. Education: Bachelor’s degree in computer science, Information Systems, Statistics, Math, or a comparable field (or equivalent).

What you’ll own

• Define and own the end-to-end architecture of the N&E ML platform spanning ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios, including authoring architecture documents, driving reviews, and overseeing implementation for scalability, reliability, and alignment with platform standards.
• Identify, scope, and prioritize the most impactful and time-sensitive ML workstreams across the N&E portfolio, breaking down and sequencing complex initiatives while proactively surfacing risks to leadership with a metrics-driven approach.
• Drive the design and evolution of infrastructure that supports the full ML lifecycle across diverse content types and brands, including data pipelines, workflow orchestration, feature stores, batch training, and low-latency online serving, with a focus on reliability, quality, and operational excellence.
• Stay current on ML, AI, and data engineering trends and champion adoption of new technologies and patterns across the portfolio, including recommendation systems, LLMs, RAGs, object detection, and autogenerated content tagging.
• Own and communicate production incident response during weekly leadership meetings, reinforcing engineering processes and leading a culture of reliability, observability, and continuous improvement.
• Contribute to the broader Machine Learning community across Disney Entertainment & ESPN, influencing engineering standards, cross-org programs, and best practices beyond the N&E ML team.
• Lead metrics-driven programs that connect platform investment to measurable guest experience and business outcomes across all brands.
• Mentor and elevate senior engineers by fostering ownership, technical rigor, and continuous learning.

What you bring

• Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field, and/or equivalent work experience.
• 10+ years building and operating ML engineering systems in production environments, with experience owning large, complex problem spaces.
• Deep expertise in data science, deep learning algorithms, and statistical methods applied to real-world, large-scale engineering problems.
• Demonstrated experience owning architecture across a significant platform or product domain, including authoring architecture documents, driving reviews, and leading implementation.
• Proven ability to drive measurable improvements in ML platform capabilities, personalization quality, or recommendation system performance.
• Experience designing and evolving backend microservices for large-scale distributed systems using REST.
• Strong cloud infrastructure expertise, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).
• Hands-on experience with big data technologies such as Databricks, Spark, Kinesis, and Kafka.
• Experience leading incident response for high-priority incidents and driving reliability programs across a team or platform.
• Active participation in cross-organizational engineering communities, standards-setting, and architectural governance.
• Track record as a metrics-driven technical leader connecting engineering decisions to business outcomes.
• Exceptional communication, influence, and collaboration skills, comfortable presenting to and aligning senior leadership and cross-functional stakeholders.
• Experience working in Agile/Scrum environments with strong prioritization and stakeholder management.

Technologies you’ll work with

REST, AWS, Step Functions, Lambda, Glue, SQS, SNS, Personalize, Databricks, Spark, Kinesis, Kafka, LLMs, RAGs, object detection, LangGraph, AutoGen, CrewAI, Claude, Cursor, GitHub Copilot, MLflow, SageMaker, Vertex AI, Agile/Scrum.

Preferred qualifications

• Experience with agentic AI workflows and frameworks (e.g., LangGraph, AutoGen, CrewAI) applied to automate complex ML and data engineering tasks.
• Familiarity with AI-assisted development tools such as Claude, Cursor, or GitHub Copilot to accelerate software development and engineering productivity.
• Familiarity with prompt engineering, fine-tuning, and evaluation frameworks for large language models in production environments.
• Experience with MLOps platforms and modern model lifecycle management tools (e.g., MLflow, SageMaker, Vertex AI).