Lead Machine Learning Engineer, Ads Research

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.

This position will be responsible for working across multiple machine learning areas with primary focus on specialization in generative AI applications, including generative mixed media, language models, and other agentic multimodal technologies.  Areas of work may include generative video, generative image, generative audio, chatbots, LLM applications, and mixed agentic workflows.  Work will additionally include traditional machine learning applications as well, including development of classical ML models to optimize advertisement marketplace operations.

Our mission is to advance AI and machine learning capabilities across Ad Platform by delivering scalable, high impact AI/ML and data science solutions that enhance generative advertisement creation and enhancement, as well as supporting efforts in more traditional AI application spaces such as Ad marketplace optimization, forecasting, and related ML and generative AI experimentation.

We are seeking a Lead Machine Learning Engineer to join this innovative team. This role offers a unique leadership opportunity for an experienced ML engineer who thrives at the intersection of technical excellence, emerging technology, strategic impact, and cross-functional collaboration, across both generative AI and traditional ML applications.

WHAT YOU’LL DO

• Develop, optimize, and productionize innovative technologies in generative AI (mixed media, video, and agentic LLM applications) as well as in traditional ML modeling applications.
• Create, evaluate, improve, optimize technologies
• Drive innovation and apply state of the art AI and machine learning across advertising domains, including inventory forecasting, ad experience, ad pacing, pricing, targeting, and efficient ad delivery.
• Invent and iterate on novel solutions to complex advertising challenges with rapid prototyping and deployment cycles.
• Design, build, and scale robust ML systems that power core ad platform capabilities
• Champion engineering excellence through best practices in code quality, system design, and operational reliability.
• Mentor and support junior engineers, fostering a culture of continuous learning and technical growth.

WHAT TO BRING

• Bachelor's in computer science or equivalent experience.
• Prior experience rigorously developing, researching, and/or productionizing any of the following generative AI modeling or AI-based editing domains: image, video, mixed media, audio, LLMs, or agentic flows.  For example: experience with diffusion models, flow models, similar generative techniques, agentic applications, etc.
• Very strong interest to self-teach via publications and training resources in generative modeling including in generative video and diffusion modeling.
• Experience creating ML datasets (especially in computer vision or generative AI) or developing rigorous quality evaluation processes or data labeling processes.  Must include an appreciation for the importance of rigorous quality evaluation processes.
• Experience developing language-processing applications via LLMs or agentic flows.
• Experience in rapid creative prototyping with generative AI is a plus, such as examples of rapid development of creative generative AI prototyping in research labs, hackathons, etc.
• Minimum 7 years of hands-on experience developing and deploying large-scale machine learning systems.
• Strong knowledge of AI/ML technologies, mathematics and statistics.
• Excellent communication, collaboration skills, and a strong teamwork ethic with both technical and non-technical audiences.
• Strong foundations in algorithms, data structures, and numerical optimization with experience in programming languages such as Python (primary), Java and SQL
• Familiarity with deep learning tools and frameworks such as TensorFlow, Pytorch, Jax, Hugging libraries etc.
• Expert knowledge with traditional (tabular) ML modeling and methods.
• Proven proficiency in deep learning methodologies, fine tuning, and transformer architectures.
• A proven track record of thriving in a fast-paced, data-driven, and collaborative work environment.
• Experience working closely with UX and front end designers building production generative AI products.

NICE-TO-HAVES

• MS or PhD (preferred) in computer science or equivalent experience.
• Experience with multimodal models and embedding techniques.
• Computer vision or visual content understanding experience.
• Experience in digital video advertising or digital marketing domain. 
• Diffusion model or generative AI controls research experience.  (Otherwise strong interest to learn).

Location: Seattle / Santa Monica / Glendale

#DISNEYTECH

The hiring range for this position in Santa Monica, CA is $171,600 to $230,100 per year and in Seattle is $179,700 to $241,000. 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.