Lead Machine Learning Engineer - News

ESPN

Glendale (CA)

On-site

USD 142,000 - 190,000

Full time

16 hours ago

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Job summary

Disney Entertainment & ESPN Technology is seeking a Lead Machine Learning Engineer to shape the News ML Platform. You will drive scalable learning, inference, and monitoring, partnering with product, data, and engineering teams to deliver personalized guest experiences across ABC News, Good Morning America, and local outlets.

You’ll guide the technical direction, develop infrastructure, and ensure low-latency, high-quality content delivery while advancing ML capabilities and algorithms for a

Qualifications

Bachelor’s degree in computer science or related field or equivalent work experience.
7+ years of software engineering experience.
5+ years hands-on experience deploying ML systems in production.
Expertise in data science, deep learning, or statistics.
Comfort with building backend microservices and cloud infra.

Responsibilities

Own complex technical initiatives end-to-end from design to production deployment and operations.
Design infrastructure for ML data pipelines, feature libraries, and orchestration.
Drive ML-driven solutions for recommendations, detection, tagging, and RAGs.
Collaborate with product, editorial, and engineering teams to translate requirements into robust solutions.
Promote code quality, testing, CI/CD, observability, and incident response.
Mentor engineers and foster a collaborative culture.

Skills

Machine learning

Leadership

Agile/Scrum

Communication

Education

Bachelor’s degree in CS or related

7+ years software engineering

Tools

AWS

Spark

Databricks

Kinesis

Kafka

REST APIs

Job description

Disney Entertainment & ESPN Technology On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world.

Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.
Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.
Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.

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.

Job Summary

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 Lead 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 And Duties Of The Role

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

Required Education, Experience/Skills/Training

Minimum and Preferred. Inclusive of Licenses/Certs (include functional experience as well as behavioral attributes and/or leadership capabilities)

Basic Qualifications

Bachelor’s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience
7+ years of software engineering experience
5+ years of hands‑on experience developing and deploying machine learning systems in production
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.

Disclaimer

This position is with Disney Entertainment & Sports LLC, which is part of a business we call Disney Entertainment and ESPN Product & Technology.

Disney Entertainment & Sports LLC is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.

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