Lead Machine Learning Engineer - ESPN+ Personalization
応募 後で応募 Job ID 10121018 勤務地-都市 サンフランシスコ, カリフォルニア州, アメリカ合衆国 / ニューヨーク, ニューヨーク州, アメリカ合衆国 / シアトル, ワシントン州, アメリカ合衆国 勤務地-国 Disney Entertainment and ESPN Product & Technology 掲載日 2025/06/16仕事内容:
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:
1. 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.
2. 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.
3. Innovation: We develop and implement groundbreaking products and techniques that shape industry norms and solve complex and distinctive technical problems.
Job Summary:
Product Engineering is a unified team responsible for the engineering of Disney 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 next-generation streaming platform. We are building a foundational ML team that will power the personalization experience for millions of users.
We are seeking a Lead Machine Learning Engineer to take ownership of major components of the end-to-end personalization system. In this role, you will lead 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:
Lead 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 continuous 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 within 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 New York, 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 base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related 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.
その他:
DISNEYTECHDisney Entertainment and ESPN Product & Technology について:
The Walt Disney Company について:
The Walt Disney Companyは、その子会社・関連会社とともに、多様性あふれる国際企業として、Disney Entertainment、ESPN、Disney Experiencesの3事業を柱に、ファミリー向けエンターテインメントとメディアの世界をけん引しています。1920年代に小さなアニメ・スタジオとしてスタートしたDisneyは、今日のエンターテインメント業界において卓越した存在となりました。ディズニーは今後も、子供から大人まで、ご家族のだれもが楽しめる一流の物語や体験を生み出し続けます。Disneyのストーリーやキャラクター、体験は、世界中のあらゆる場所の消費者やお客様に届けられています。当社は40カ国以上で、従業員とキャストメンバーが一丸となり、世界的にも地域的にも歓迎されるエンターテインメント体験を創出しています。
このポジションは Disney Streaming Technology LLC という事業部門の一つである Disney Entertainment and ESPN Product & Technologyでのお仕事です。
Disney Streaming Technology LLC は機会均等雇用主です。応募者は、人種、宗教、肌の色、性別、性的指向、ジェンダー、性自認、性表現、国籍、家柄、年齢、配偶者の有無、軍役経験の有無やその地位、健康状態、遺伝情報や障がい、または連邦法や州法、地方法で禁止されているその他の法的根拠に関係なく、雇用の検討対象となります。Disneyは、すべての人々のアイデアと決断が、成長、革新、最高のストーリーの創造に役立ち、絶えず進化する世界において、価値ある存在になれるよう支援するビジネス環境を支持します。