Senior Machine Learning Engineer - News

Senior Machine Learning Engineer on the News ML Platform within Disney Entertainment and ESPN Product & Technology, onsite in New York, shaping scalable real-time personalized content across ABC News, Good Morning America, and local stations.

Responsibilities

• Lead end-to-end technical initiatives from design through production rollout and ongoing reliability
• Design and build ML infrastructure covering the full lifecycle, including data pipelines, workflow orchestration, data discovery and quality tooling, and feature libraries
• Develop data and ML powered solutions for diverse engineering use cases including recommendations, object detection, autogenerated tagging, and retrieval augmented generation (RAG) solutions
• Collaborate with product, editorial, and engineering stakeholders to translate business needs into solid technical solutions
• Prioritize initiatives and technical workstreams to maximize impact and timeliness, while proactively identifying and communicating risks and mitigating them to ensure successful execution
• Promote engineering best practices in code quality, testing, CI/CD, observability, and incident response
• Mentor engineers, fostering ownership, collaboration, and continuous improvement
• Contribute to technical documentation and facilitate knowledge sharing across teams

Requirements

• Bachelor’s degree in computer science, information systems, statistics, math, or a related field, or equivalent work experience
• 5+ years building and operating production-grade ML engineering systems
• Strong background in data science, deep learning techniques, or statistical methods to address practical engineering challenges
• Experience across the full predictive stack, from data collection and analysis to feature engineering, batch training, and low-latency online serving
• Proficiency in designing and building backend microservices for large-scale distributed systems using REST
• Experience with cloud infrastructure, preferably AWS, including Step Functions, Lambda, Glue, SQS, SNS, and Personalize
• Familiarity with building and deploying Spark and ML pipelines
• Hands-on experience with big data platforms such as Databricks, Kinesis, and Kafka
• Proven leadership, coaching, and mentoring abilities, capable of guiding a team toward business objectives
• Experience with observability tools for metrics, logging, and monitoring, including Datadog
• Background in Agile or Scrum development approaches
• Strong communication skills and a collaborative mindset in a fast-paced, guest-focused setting

Technologies

• AWS
• Step Functions
• Lambda
• Glue
• SQS
• SNS
• Personalize
• Spark
• Databricks
• Kinesis
• Kafka
• REST
• Datadog