Lead Machine Learning Engineer, Ads Research

Join Disney Entertainment and ESPN Product & Technology as a Lead Machine Learning Engineer for Ads Research. This leadership role centers on generative AI and traditional ML to advance Disney’s advertising products and ad marketplace experiences. You will guide development, deployment, and cross-functional collaboration across product, design, and engineering teams. The position is onsite in Seattle, Santa Monica, or Glendale, with a competitive salary range of USD 171,600 - 241,000 per year. Benefits include bonus and long-term incentive units, medical coverage, and financial benefits.

Responsibilities

• Develop, optimize, and productionize innovative technologies in generative AI across mixed media, video, and agentic LLM applications, alongside traditional ML modeling.
• Create, evaluate, improve, and optimize technologies to meet product goals.
• Drive innovation by applying state of the art AI and ML 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.

Requirements

• Bachelor’s degree in computer science or equivalent experience.
• Track record of rigorously developing, researching, or productionizing generative AI modeling or AI-based editing domains, including image, video, mixed media, audio, LLMs, or agentic flows; experience with diffusion models, flow models, or related techniques is beneficial.
• Strong interest in self-directed learning through publications and training resources in generative modeling, including generative video and diffusion modeling.
• Experience creating ML datasets (especially in computer vision or generative AI) or establishing rigorous quality evaluation and data labeling processes.
• Experience developing language-processing applications via LLMs or agentic flows.
• Experience in rapid creative prototyping with generative AI is a plus, such as work from research labs or hackathons.
• Minimum 7 years of hands-on experience building and deploying large-scale ML systems.
• Strong knowledge of AI/ML technologies, mathematics, and statistics.
• Excellent communication and collaboration skills, with the ability to work with both technical and non-technical stakeholders.
• Solid foundations in algorithms, data structures, and numerical optimization; proficient in Python (primary), Java, and SQL.
• Familiarity with deep learning frameworks such as TensorFlow, PyTorch, Jax, and Hugging libraries.
• Expertise in traditional (tabular) ML modeling and methods, with proven proficiency in deep learning, fine tuning, and transformer architectures.
• Demonstrated success in fast-paced, data-driven, collaborative environments, and experience working with UX and frontend designers on production generative AI products.

Technologies: Python, Java, SQL, TensorFlow, PyTorch, Jax, Hugging libraries

Benefits

• Bonus and/or long-term incentive units
• Medical benefits
• Financial benefits

Nice-to-haves

• MS or PhD in computer science or equivalent experience (preferred).
• 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, or strong interest to learn.

Location

Seattle, Santa Monica, Glendale (onsite)