Disney Entertainment and ESPN Product & Technology offers an on-site Senior Machine Learning Engineer role in New York with a competitive annual compensation range of $148,700 to $199,400. This individual contributor position focuses on developing, productionizing, and optimizing personalization and recommendation algorithms for Disney+ and Hulu, working closely with Engineering, Product, and Data teams on site.
As part of a global technology team, you will help shape user experiences across Disney streaming platforms by applying advanced machine learning methods to drive personalization, discovery, and engagement.
Company overview
Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more, building the technological backbone for Disney’s media business worldwide. The team blends technology with creativity to create world-class products, accelerate storytelling, and enable scalable innovation for our businesses. We are storytellers and builders, entertainers and engineers, collaborating across The Walt Disney Company’s media portfolio to strengthen the technology foundation and consumer touchpoints serving millions of people around the world.
Why you might love working here
- Building the future of Disney’s media: technologists design and build products and platforms that will power media, advertising, and distribution for years to come.
- Reach, scale and impact: Disney’s technology and products serve as a gateway for fans to connect with brands and stories at global scale across Disney+, Hulu, ESPN, ABC, and more.
- Innovation: we develop and implement novel approaches that influence industry norms and tackle distinctive technical challenges.
Responsibilities
- Algorithm development and maintenance: apply modern machine learning methods to build personalization, recommendation, and predictive systems; maintain production-grade algorithms and communicate methodologies clearly to technical and non-technical stakeholders.
- Feature engineering and optimization: design and operate ETL pipelines with orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines for petabyte-scale datasets.
- Development best practices: uphold and create standards for algorithm development, testing, and deployment.
- Collaborate with product and business stakeholders: identify new personalization opportunities and partner with data teams to improve data collection, experimentation, and analysis.
Requirements
- 5+ years of experience developing machine learning models, performing large-scale data analysis, or data engineering.
- 5+ years writing production-level, scalable code in Python and SQL.
- 3+ years developing algorithms for deployment to production systems.
- Deep understanding of modern machine learning methods, models, and their mathematical underpinnings.
- Experience deploying and maintaining pipelines and building big-data solutions with Databricks, S3, and Spark.
- Ability to assess ML problem complexity and apply simple, effective approaches when appropriate.
- Strong written and verbal communication skills.
- MS or PhD in statistics, math, computer science, or a 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 data governance principles.
- Experience loading and querying cloud-hosted databases.
Technologies
- Python
- SQL
- Airflow
- Jenkins
- Databricks
- S3
- Spark
Benefits
- Medical benefits
- Financial benefits
- Bonus and long-term incentive units
Role Location
On-site role requiring four days in-person at the designated office location.
