reputed company Machine Learning Engineer - ESPN+ Personalization

reputed company Entertainment and ESPN Product & Technology Technology is at the heart of reputed company’s past, present, and future. reputed company Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – reputed company working to build and advance the technological backbone for reputed company’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 reputed 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: 1. Building the future of reputed company’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. 2. reputed company, Scale & Impact: More than reputed company, reputed company’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. reputed company+. 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. 3. Innovation: We reputed company and implement groundbreaking products and techniques that shape industry norms and solve reputed company and distinctive technical problems. Job Summary: Product Engineering is a reputed company team responsible for the engineering of reputed company Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity. ESPN is building a new real-time video recommendation system as a core capability of our reputed company streaming platform. We are building a foundational ML team that will power the personalization experience for millions of users. We are seeking a reputed company Machine Learning Engineer to take ownership of major components of the end-to-end personalization system. In this role, you will reputed company the technical design and delivery of key subsystems (modeling, data pipelines, real-time serving, or online experimentation), working closely with the Principal MLE, product, infrastructure, and cross-functional partners. You will combine deep machine learning expertise with strong software engineering skills to drive production-grade ML solutions at scale. In addition, you will provide mentorship to more junior engineers and play a key role in establishing technical standards, development processes, and team culture as the team grows. Responsibilities and Duties of the Role:

• reputed company the design, development, and deployment of machine learning models for large-scale real-time short-form video recommendation.
• Architect and implement key subsystems of the end-to-end personalization pipeline, including model training, online inference, feature stores, streaming pipelines, and serving infrastructure.
• Build advanced recommendation models using deep learning, embeddings, sequence models, transformers, and multi-task learning frameworks.
• Partner with Principal ML Engineer and technical leadership to drive system architecture decisions balancing scalability, latency, accuracy, and maintainability.
• Conduct deep data analyses on user interactions to identify optimization opportunities and drive reputed company model improvements.
• Drive ML experimentation processes, A/B testing, and evaluation frameworks to validate model performance.
• Establish and enforce ML engineering best practices across model development, deployment, monitoring, and governance.
• Mentor and provide technical guidance to other ML engineers, contributing to capability building reputed company the team.
• Collaborate closely with product managers, data scientists, engineers, and infrastructure teams to align technical execution with business goals.

Required Education, Experience/Skills/Training: Basic Qualifications:

• Demonstrated ownership of end-to-end ML system components with successful production launches.
• Strong applied ML expertise with experience in personalization, recommendation systems, ranking models, and/or predictive modeling.
• Proficiency with modern ML frameworks such as TensorFlow, PyTorch, or similar.
• Experience with real-time feature stores, streaming data pipelines, and online inference architectures.
• Strong software engineering skills, with experience in distributed systems, data pipelines, and cloud platforms (AWS, GCP, Azure).
• Excellent communication, collaboration, and technical leadership skills, including mentorship experience.
• Experience partnering with cross-functional teams (product, infra, data science) to deliver ML-powered product features.

Preferred qualification:

• Experience building real-time recommendation systems for content feeds, media platforms, or short-form video.
• Familiarity with ranking models, retrieval systems, approximate nearest neighbor search (ANN), and embedding management at scale.
• Knowledge of real-time personalization challenges including cold start, feedback loops, delayed labels, and exploration-exploitation tradeoffs.
• Experience with experimentation platforms (A/B tests, multi-armed bandits, reinforcement learning).
• Experience operating in startup-like or 0→1 product development environments.
• Ability to identify technical risks, balance tradeoffs, and drive pragmatic solutions under ambiguous product requirements.

Experience with:

• 7+ years of hands-on experience building and deploying machine learning models into production systems.

Required Education:

• Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience

#DISNEYTECH The hiring range for this position in reputed company, NY & Seattle, WA is $172,300-$231,100 per year, in San Francisco, CA is $183,700.00-$246,400.00 per year and in Los Angeles, CA is $164,500.00 to $220,600.00 per year. The reputed company pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-reputed company 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. Apply tot his job Apply To this Job