Machine Learning Engineer II

$118,000 - $158,200/Yr

Disney - Seattle, WA

Full-time - Mid Level

Seattle, WA

Motion Picture and Sound Recording Industries

About the position

The position involves working as an Individual Contributor in the content recommendations team at Disney Entertainment & ESPN Technology. The role focuses on developing and optimizing recommendation and personalization algorithms for Disney's streaming services, including Disney+ and Hulu. The individual will collaborate with various teams to apply machine learning methods to enhance user experience and meet strategic product goals.

Responsibilities

• Utilize cutting edge machine learning methods to develop and implement algorithms for personalization, recommendation, and other predictive systems.
• Maintain algorithms deployed to production and explain methodologies to technical and non-technical teams.
• 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.
• Maintain existing and establish new algorithm development, testing, and deployment standards.
• Identify and define new personalization opportunities and work with other data teams to improve data collection, experimentation, and analysis.

Requirements

• 3+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience.
• Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
• 3+ years writing production-level, scalable code (e.g. Python, Scala).
• 3+ years of experience developing algorithms for deployment to production systems.
• In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings.
• Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in 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 as appropriate.
• Strong written and verbal communication skills.

Nice-to-haves

• 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.

Benefits

• Medical benefits
• Financial benefits
• Bonus and/or long-term incentive units may be provided as part of the compensation package.