Senior Machine Learning Engineer - News

Senior Machine Learning Engineer

Technology is at the heart of Disney's past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney's media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company's media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.

Here are a few reasons why we think you'd love working here:

• Building the future of Disney's media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
• Reach, Scale & Impact: More than ever, Disney's technology and products serve as a signature doorway for fans' connections with the company's brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
• Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.

The News ML team is responsible for building robust data pipelines and advanced machine learning platforms that deliver personalized experiences to users across ABC News, Good Morning America, and local news stations. Our services leverage machine learning models to enable real-time content personalization and targeted distribution across web, mobile, and connected TV platforms, ensuring that users receive the most relevant and engaging news content tailored to their interests. Our mission is to drive seamless, resilient, and low-latency personalized content delivery at scale, while continuously advancing our ML infrastructure and recommendation algorithms.

As a Senior Machine Learning Engineer, you will play a leading role in shaping the technical direction of the News ML Platform. You will drive infrastructure for scalable learning, inference, and monitoring, conduct in-depth data exploration and analysis, and collaborate across product, data, and engineering teams to power exceptional, personalized guest experiences. Your work will directly support strategic initiatives to help shape the roadmap for algorithmic innovation while ensuring that solutions are scalable, impactful, and aligned with stakeholder needs.

Responsibilities

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

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Statistics, Math, or comparable field of study, 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
• Comfortable operating at all levels of 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 inspire and empower a team towards achieving 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 commitment to collaboration in a fast-paced, guest-focused environment

The hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Glendale, CA is $141,900 - $190,300. The base pay actually offered will take into account internal equity and also may vary depending on the candidate's geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.