Design, build, and operate highly scalable software systems and services that support content discovery, personalization, and recommendation experiences
Develop and maintain distributed data processing platforms and service architectures that power both online and offline product workflows
Build foundational platform capabilities, including feature serving, model inference integration, experimentation infrastructure, and recommendation delivery services
Design reliable APIs and service interfaces that enable personalization capabilities across multiple ESPN products and surfaces
Lead architecture and technical design efforts for systems that must operate with high availability, low latency, and large-scale traffic demands
Partner with Machine Learning, Data Science, Product, and Platform Engineering teams to translate business objectives into scalable software solutions
Establish engineering standards, operational best practices, monitoring, observability, and reliability mechanisms across critical systems
Drive technical strategy and execution for next-generation personalization platforms and services
Mentor engineers and influence engineering practices across teams through technical leadership, design reviews, and architectural guidance

7+ years of experience building and maintaining production-grade data pipelines and distributed data processing systems
Strong experience with modern data processing frameworks such as Spark, Flink, Beam, Kafka Streams, or equivalent
Experience designing and implementing real-time streaming data pipelines
Proficiency with SQL and schema design for large-scale analytical datasets
Familiarity with cloud data platforms (e.g., AWS) and modern data infrastructure components (e.g., data lakes, data warehouses, feature stores)
Experience supporting ML workflows (model training pipelines, feature engineering, data validation)
Strong knowledge of data quality frameworks and best practices, with hands-on experience using Databricks, Snowflake, and Apache Airflow for data pipeline orchestration and validation
Solid software engineering skills with experience in Python, Java, Scala, or similar languages
Strong problem-solving skills and ability to work independently in a fast-paced environment

A bonus and/or long-term incentive units may be provided as part of the compensation package
Full range of medical, financial, and/or other benefits

Lead Product Software Engineer – ML Data Systems

Key skills