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Manager, Machine Learning Engineering - Ad Platforms
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Manager, Machine Learning Engineering - Ad Platforms
- United States
- United States
À propos
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 organization within Disney Entertainment and ESPN Technology is fully responsible for building, enhancing and maintaining high-performance, distributed, microservice-based Advertising Platform across all of Disney online properties, including Hulu and ESPN+. We build and maintain proprietary technology, ranging from ad serving and ad delivery, campaign management, reporting as well as all the integrations internal and external that come with evolving and maintaining a best-in-class video advertising business. 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. Daily, you should bring: A willingness and desire to effectively communicate and collaborate across teams and systems on architecture, design, and implementation. A passion for mentoring, learning, and taking on new challenges. A proven ability to work with product teams to translate requirements into well-defined technical implementations, as well as the ability to define technical and operational metrics to measure system health. A keen eye for potential optimizations and enhancements. Kindness and pragmatic optimism. A deep understanding of model development cycles and AI tool usage Responsibilities and Duties of the Role: Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection. 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. Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders. 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. 8+ years of relevant industry experience, with at least 2-3 years in a people-management or technical leadership role. 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).
Compétences linguistiques
- English
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