Senior Machine Learning Engineering Manager, Ad Platforms

Senior Machine Learning Engineering Manager 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. 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 various aspects of ad serving. We are seeking a Senior Manager Machine Learning to join this innovative team. This role offers a unique leadership opportunity for an experienced ML/AI and people leader who thrives at the intersection of technical excellence, strategic impact, and cross-functional collaboration. You will apply your battle-tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices which are aligned in close collaboration with the ML team in the US highlighting cross-functional collaboration. Responsibilities and Duties of the Role: Lead, mentor and guide senior individual contributors and managers across data scientists, machine learning and AI engineers teams to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection. Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders. Lead by example and always strive to improve the design for more scalable, cleaner, and decoupled implementations. Drive adoption of best practices in model development, code quality, testing, and documentation. Solid understanding and usage of automated tools (AI) while adhering to company policy. Oversee end-2-end machine learning workflow, including data collection, model development, deployment and modeling. These are expected to be aligned with the larger platform strategy and tools in collaboration with the global teams to stay consistent across Ad Platforms. Foster innovation by exploring new ML techniques, tools, and technologies. Communicate strategies, progress, and results to leadership and cross-functional teams. Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards. Develop partnerships across the organization to identify and prioritize high-impact ML opportunities. Available for On-Call rotations based on the team's escalation policy and support schedule for ML/AI solutions Basic Qualifications: Bachelor's or master's degree in computer science, Engineering, Mathematics, Statistics, or a related field. 10+ years of relevant industry experience, with at least 5 years in people-management managing senior ICs and managers. Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling. Proven experience designing, building, and deploying scalable machine learning models and systems in production. Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices Advanced programming proficiency (e.g., Python, Java, or similar); experience with ML/DL frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face). Experience building, fine-tuning, evaluating, and deploying LLM-based systems (e.g., RAG, prompt engineering, model optimization) Demonstrated ability to lead global teams and collaborate across organizational boundaries. Preferred Qualifications: Domain knowledge in the Ad Tech industry Experience working with large-scale data and distributed systems. Knowledge of cloud platforms (e.g., AWS, GCP, Azure) and MLOps pipelines. Track record of innovation and contributions to the ML/AI community (publications, talks, open source).