Job Posting Title:

Senior Machine Learning Engineer

Req ID:

10140852

Job Description:

Disney Entertainment and ESPN Product & Technology

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.

Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.

Job Summary:

The Ad Platform Engineering organization within Disney Entertainment and ESPN Product & Technology is responsible for building, enhancing, and operating a high-performance, distributed, microservice-based digital advertising platform. This platform powers billions of real-time ad decisions daily across Disney’s video-on-demand and live TV properties, including Hulu, Disney+, ESPN, and more.

Within Ad Platform Engineering, the Programmatic teams build and maintain Disney’s programmatic advertising suite of products and services that comprise Disney's Real-time Ad Exchange (DRAX). DRAX is an award-winning, proprietary supply-side platform (SSP) that enables programmatic deal configuration and integrates demand from multiple third-party sources into Disney’s ad server in real time.

As a Senior Machine Learning Engineer, you will design, build, and operate production machine learning systems that directly impact revenue, efficiency, and viewer experience at global scale. This is a hands-on, production-focused role, ideal for an experienced ML engineer who enjoys owning complex systems end-to-end, partnering closely with product and engineering teams, and delivering measurable impact in low-latency, high-throughput environments operating at billion-request-per-day scale.

This role is not research-only. Success is measured by production outcomes, system reliability, model performance, and continuous iteration based on data and feedback.

Daily, you should bring:

Strong technical ownership and accountability for production ML systemsEffective collaboration and communication across engineering, product, and data partnersComfort operating in ambiguity and translating loosely defined problems into scalable solutionsA continuous improvement mindset with attention to performance, reliability, and costThe ability to define and use technical and operational metrics to measure system and model health

Responsibilities:

Apply modern machine learning techniques to advertising use cases such as inventory forecasting, pricing, targeting, and efficient ad deliveryDesign, implement, and iterate on ML solutions from experimentation through production deployment and ongoing optimizationBuild and scale ML architectures that balance model quality, latency, throughput, reliability, and costDesign and maintain feature pipelines and feature stores supporting both real-time inference and offline trainingOwn major components of the model lifecycle, including experimentation, validation, deployment, monitoring, and iterationAnalyze experimental results and partner with product and engineering stakeholders to support data-informed decisionsEnsure models are observable, debuggable, and explainable in production environmentsImplement monitoring for model performance, drift, bias, and overall system healthContribute to engineering excellence through high-quality code, sound system design, and operational best practicesProvide technical guidance through code reviews, design discussions, and knowledge sharing

Basic Qualifications:

Bachelor's degree in Computer science or related field of study5+ years of software engineering experienceMinimum 3 years of hands-on experience developing and deploying machine learning systems in productionStrong knowledge of machine learning fundamentals, mathematics, and statisticsExperience operating ML systems in low-latency, high-throughput environmentsStrong communication and collaboration skills with both technical and non-technical partnersSolid foundations in algorithms, data structures, and numerical optimizationProficiency in Python (primary), with experience in Java and SQLExperience with modern ML frameworks and tooling such as TensorFlow, PyTorch, and Hugging FaceExperience with one or more of the following:Deep learning methodologies (e.g., sequence-based or representation learning models)Transformer architectures (e.g., BERT, GPT, ViT) for NLP and/or visionMultimodal embedding techniques across text, image, audio, or structured dataLarge language models and related evaluation methodologiesRetrieval-augmented generation (RAG) architecturesExperience building systems on cloud-native infrastructure and distributed platformsProven ability to thrive in a fast-paced, data-driven, and collaborative environment

Preferred Qualifications:

Experience in digital video advertising or the digital marketing domainExperience with programmatic advertising or real-time bidding platformsMS or PhD (preferred) in Computer Science or equivalent practical experienceThe hiring range for this position in Glendale, California is $141,900 to $190,300 per year, Santa Monica, California is $141,900 to $190,300 per year, and Seattle, WA is $148,700 to $199,400 per year. 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.

Job Posting Segment:

Ad Platforms

Job Posting Primary Business:

AP - Software Engineering

Primary Job Posting Category:

Machine Learning

Employment Type:

Full time

Primary City, State, Region, Postal Code:

Glendale, CA, USA

Alternate City, State, Region, Postal Code:

USA - CA - 2450 Broadway, USA - WA - 925 4th Ave

Date Posted:

2026-01-26