Senior Machine Learning Engineer - News

Benefits

Disney Entertainment and ESPN Product & Technology offer an onsite opportunity in New York, NY with a competitive salary range of USD 148,700 to 199,400 per year. In addition to compensation, the role includes bonus and/or long-term incentive units, medical benefits, financial benefits, and a broad set of other perks that support career growth and work-life balance.

• bonus and/or long-term incentive units
• medical benefits
• financial benefits
• other benefits

Responsibilities

• Own complex technical initiatives end to end, from architectural design to production deployment and ongoing operational excellence
• Design and build infrastructure that supports the full machine learning lifecycle, including data pipelines, workflow orchestration, data discovery and quality tools, and feature libraries
• Develop data and ML driven solutions for diverse engineering use cases such as recommendation systems, object detection, autogenerated tagging, and RAGs
• Partner with product, editorial, and engineering stakeholders to translate business requirements into robust technical solutions
• Strategically prioritize initiatives and workstreams to deliver high-impact, time-sensitive outcomes while proactively identifying and mitigating risks
• Champion engineering best practices across code quality, testing, CI/CD, observability, and incident response
• Mentor and coach engineers, fostering ownership, collaboration, and continuous improvement
• Contribute to technical documentation and promote knowledge sharing across teams

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Statistics, Math, or a comparable field, and/or equivalent work experience
• 5+ years of experience building and operating ML engineering systems in production environments
• Expertise in data science, deep learning algorithms, or statistical methods to solve real-world engineering problems
• Comfort working across the predictive stack, including data collection, data analysis, feature engineering, batch training, and low-latency online serving
• Experience designing and developing backend microservices for large-scale distributed systems using REST
• Experience with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)
• Familiarity with developing and deploying Spark and ML pipelines
• Hands-on experience with big data technologies such as Databricks, Kinesis, Kafka
• Proven leadership, coaching, and mentoring skills with the ability to empower a team toward business goals
• Experience with observability tools for metrics, logging, and monitoring such as Datadog
• Experience working in Agile/Scrum development environments
• Excellent communication skills and a collaborative approach in a fast-paced, guest-focused environment

Technologies

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