Sr Machine Learning Engineer

Job Requirements

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.

Job Summary ( Describe what the person will do in the role - how he/she will impact the organization. )

ESPN is investing in next-generation sports personalization and recommendation experiences across its digital products. We are seeking a Senior Machine Learning Engineer who will focus on the design, development, and productionization of advanced deep learning models for large-scale recommendation and ranking systems.

This is a model-focused engineering role. The successful candidate will bring strong foundations in deep learning theory and modern recommender-system architectures, together with the software engineering depth to translate research and prototypes into reliable, production-grade, performance-optimized models. The role will own model architecture decisions, training methodology, offline evaluation, inference optimization, and the model code required for dependable online serving, while partnering with platform and infrastructure teams on deployment and operations.

Responsibilities and Duties of the Role: ( Summarize job responsibilities, core deliverables and major duties. What is required for the position to exist? )

• Lead the design and implementation of advanced deep learning models for retrieval, ranking, and personalization, including embedding-based, sequence, transformer, and multi-task architectures.

• Translate product and personalization objectives into model formulations, loss functions, sampling strategies, feature representations, and evaluation plans grounded in machine learning theory.

• Develop production-grade training and inference code with strong standards for correctness, modularity, testing, reproducibility, and maintainability.

• Optimize models for online performance, including latency, throughput, memory efficiency, and cost, using techniques such as distillation, quantization, pruning, batching, compilation, and efficient architecture design where appropriate.

• Own the model productionization path from prototype through offline validation and online integration, ensuring consistency between training and inference behavior.

• Design rigorous offline experiments, ablation studies, and evaluation…