Lead Machine Learning Engineer

Role Location This is an on‑site role requiring 4 days in‑person at a designated office location. Organizational Context Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more, working to build and advance the technological backbone for Disney’s media business worldwide.

We marry technology with creativity to build world‑class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. Why Work Here Building the future of Disney’s media: designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come. Reach, Scale & Impact: our technology and products serve as a signature doorway for fans’ connections with the company’s brands and stories—Disney+, Hulu, ESPN, ABC, ABC News, and many more.

Innovation: developing and implementing groundbreaking products and techniques that shape industry norms and solve complex technical problems. Product Engineering Overview We are responsible for engineering Disney Entertainment & ESPN digital and streaming products and platforms, including product engineering, media engineering, quality assurance, personalization, commerce, lifecycle, and identity. Job Summary Our team designs and builds models that directly shape the user experience—powering personalization and engagement across Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu.

With a strong product mindset and focus on usability, we ensure every ML‑driven product enhances how users discover, interact, and enjoy our experiences. As an Individual Contributor, you will lead recommendation and personalization algorithm research, development, and productionization, and coordinate stakeholder expectations. Responsibilities And Duties Algorithm development and maintenance: utilize cutting‑edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms in production and serve as the point person explaining methodologies.

Feature engineering and optimization: develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte‑scale datasets. Development best practices: maintain existing and establish new algorithm development, testing, and deployment standards. Collaborate with product and business stakeholders: identify and define new personalization opportunities and work with other data teams to improve data collection, experimentation, and analysis.

Required Education, Experience, Skills, and Training (Basic Qualifications) 7+ years of experience developing machine learning models, performing large‑scale data analysis, and/or data engineering. 5+ years writing production‑level, scalable code (Python, SQL). 3+ years of experience developing algorithms for deployment to production systems. Led complex projects and mentored team members. In‑depth understanding of modern machine learning (e.g., deep learning methods), models, and their mathematical underpinnings.

Experience deploying and maintaining pipelines and engineering big‑data solutions using technologies like Databricks, S3, and Spark. Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions. Strong written and verbal communication skills.

Preferred Qualifications MS or PhD in statistics, math, computer science, or related quantitative field. Production experience with developing content recommendation algorithms at scale. Experience building and deploying full‑stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment.

Familiar with metadata management, data lineage, and principles of data governance. Experience loading and querying cloud‑hosted databases. Experience With AWS, Databricks.

Education Bachelor’s Degree in Computer Science, Math, Statistics, or related quantitative field. Compensation The hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Santa Monica, CA is $141,900 - $190,300. Base pay may vary depending on geographic region, knowledge, skills, and experience.

A bonus and/or long‑term incentive units may be provided, in addition to the full range of medical, financial, and other benefits, depending on level and position offered. #J-18808-Ljbffr