Disney Entertainment & Sports LLC is building and evolving machine learning capabilities across its News & Entertainment portfolio, spanning brands such as ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios. In this onsite role in Glendale, CA, you will shape the technical architecture and strategic direction for the News & Entertainment ML platform, driving improvements across personalization, recommendation systems, and the infrastructure that supports reliable, production-grade ML execution.
As a Principal Machine Learning Engineer, you will lead metrics-driven initiatives, manage key engineering decisions end to end, and partner with leadership during production incident conversations to strengthen reliability and observability. The role also includes mentoring senior engineers and contributing to broader Machine Learning engineering standards across Disney Entertainment & ESPN.
Responsibilities
- Define and own the end-to-end architecture for the N&E ML platform across a large problem space; author architecture documents, guide review, and oversee implementation to ensure solutions are scalable, reliable, and aligned with platform-wide standards.
- Identify, scope, and prioritize impactful and time-sensitive ML workstreams across the N&E portfolio; decompose and sequence complex initiatives while proactively surfacing risks to leadership using a metrics-driven mindset.
- Design and evolve 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 an emphasis on reliability, quality, and operational excellence.
- Monitor industry trends in ML, AI, and data engineering, and champion adoption of new technologies and patterns across the portfolio, including recommendation systems, LLMs, RAGs, object detection, and autogenerated content tagging.
- Own and contribute to production incident discussions during weekly meetings with leadership, reinforcing the right engineering processes and helping build a culture of reliability, observability, and continuous improvement.
- Participate in and 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.
- Serve as a thought leader across business objectives and technical challenges, leading metrics-driven programs that connect ML platform investments to measurable guest experience and business outcomes across all brands.
- Mentor and elevate senior engineers by fostering ownership, technical rigor, and continuous learning, while providing leadership that helps teams rally around outcomes.
Requirements
- Bachelor’s degree in computer science, Information Systems, Statistics, Math, or a comparable field of study, and/or equivalent work experience.
- 10+ years of experience building and operating ML engineering systems in production environments, with a track record of 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 quantifiable 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 expertise with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize).
- Deep 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.
- Proven track record as a metrics-driven technical leader connecting engineering decisions to business outcomes.
- Exceptional communication, influence, and collaboration skills, including comfort presenting to and aligning senior leadership and cross-functional stakeholders.
- Experience working in Agile/Scrum environments, with strong prioritization and stakeholder management skills.
Technologies
- 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 (for example, 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 lifecycle 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 (for example, MLflow, SageMaker, Vertex AI).
Location: Glendale, CA (onsite)
Salary: USD 210,500 - 295,900 per year
