Machine Learning Engineer II

$118,000 - $158,200/Yr

Hulu - New York, NY

Full-time - Mid Level

New York, NY

Motion Picture and Sound Recording Industries

About the position

The Machine Learning Engineer II at Disney Entertainment & ESPN Technology plays a crucial role in developing and optimizing recommendation and personalization algorithms for Disney's streaming services, including Disney+ and Hulu. This position involves collaborating with various teams to apply machine learning methods that enhance user experiences and meet strategic product goals. As an individual contributor, the engineer will lead algorithm research, development, and maintenance, ensuring that the algorithms deployed are effective and aligned with company objectives.

Responsibilities

• Utilize cutting edge machine learning methods to develop and implement algorithms for personalization and recommendation 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.
• Establish and maintain algorithm development, testing, and deployment standards.
• Identify and define new personalization opportunities in collaboration with product and business stakeholders.
• Work with other data teams to improve data collection, experimentation, and analysis.

Requirements

• 3+ years of experience developing machine learning models and performing large-scale data analysis.
• Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field of study.
• 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 methods and models.
• Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and engineering big-data solutions using technologies like Databricks, S3, and Spark.
• Strong written and verbal communication skills.

Nice-to-haves

• 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.
• Familiarity with metadata management, data lineage, and principles of data governance.

Benefits

• Medical, financial, and other benefits depending on the level and position offered.
• Bonus and/or long-term incentive units may be provided as part of the compensation package.