Lead Machine Learning Engineer

$180,200 - $241,600/Yr

Unclassified - San Francisco, CA

Full-time - Mid Level

San Francisco, CA

About the position

The Machine Learning Engineer position at Disney Entertainment & ESPN Technology focuses on leading the development and optimization of recommendation and personalization algorithms. This role involves working on event-driven ML pipelines and maintaining a central feature store that supports various ML use cases. The engineer will collaborate with cross-functional teams to enhance data collection and analysis, ensuring high system availability and reliability while driving innovation in ML infrastructure.

Responsibilities

• Lead research, development, implementation, and optimization of recommendation and personalization algorithms.
• 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.
• Collaborate with product and business stakeholders to identify and define new personalization opportunities.

Requirements

• 7+ years of relevant experience developing machine learning models and performing large-scale data analysis.
• 7+ years of experience writing production-level, scalable code (e.g. Python, Scala).
• 5+ years of experience developing algorithms for deployment to production systems.
• In-depth understanding of modern machine learning methods and their mathematical underpinnings.
• Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and engineering big-data solutions using technologies like Databricks, S3, and Spark.

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.
• Familiarity with metadata management, data lineage, and principles of data governance.
• Experience loading and querying cloud-hosted databases.

Benefits

• Medical insurance coverage
• Financial benefits including bonuses and long-term incentive units
• Flexible working arrangements
• Opportunities for professional development and growth