跳至主要內容
BE YOU. BE HERE. BE PART OF THE STORY.

Machine Learning Engineer II

工作 ID 10102658 地點 纽约, 纽约州, 美國 / 圣莫尼卡, 加利福尼亚州, 美國 / 旧金山, 加利福尼亚州, 美國 / 西雅圖, 华盛顿州, 美國 有意工作的公司 Disney Entertainment & ESPN Technology 日期已公佈 Nov. 12, 2024
申請

工作概要:

On any given day at Disney Entertainment & ESPN Technology, we’re reimagining ways to create magical viewing experiences for the world’s most beloved stories while also transforming Disney’s media business for the future. Whether that’s evolving our streaming and digital products in new and immersive ways, powering worldwide advertising and distribution to maximize flexibility and efficiency, or delivering Disney’s unmatched entertainment and sports content, every day is a moment to make a difference to partners and to hundreds of millions of people around the world. A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology

  • Building the future of Disney’s media business: DE&E Technologists are designing and building the infrastructure that will power Disney’s media, advertising, and distribution businesses for years to come.

  • Reach & Scale: The products and platforms this group builds and operates delight millions of consumers every minute of every day – from Disney+ and Hulu, to ABC News and Entertainment, to ESPN and ESPN+, and much more.

  • Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.

Our team develops and maintains recommendation and personalization algorithms for Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu. As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes. This is an Individual Contributor role in content recommendations. You will be expected to lead recommendation and personalization algorithm research, development, and optimization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. You will be expected to help meet KPIs for product areas and to set and meet deadlines for external and internally facing tools, such as offline evaluation tools for pre-production algorithms. As an IC, you will also be responsible for helping to set the roadmap for algorithmic work — not only for how to approach product requests for new recommendation features, but for helping to drive larger company objectives in the areas of personalization and content recommendation.

Responsibilities:

  • Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop and implement algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams

  • Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets

  • Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards

  • Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis

  • Experience loading and querying cloud-hosted databases
  • Building streaming data pipelines using Kafka, Spark, or Flink

Basic Qualifications:

  • 3+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience

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

  • 3+ years writing production-level, scalable code (e.g. Python, Scala)

  • 3+ years of experience developing algorithms for deployment to production systems

  • In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings

  • Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark

  • Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate

  • Strong written and verbal communication skills

Preferred Qualifications:

  • MS or PhD in statistics, math, computer science, or related quantitative field

  • Production experience with developing content recommendation algorithms at scale

  • Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment

  • Familiar with metadata management, data lineage, and principles of data governance

#DISNEYTECH


The hiring range for this position in New York is $118,000.00-158,200.00 per year, in Los Angeles is $136,100.00-182,400.00 per year, in California is $123,400.00-165,400.00 per year and in Seattle is $118,000.00-158,200.00 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.

申請

關於Disney Entertainment & ESPN Technology:

Disney Entertainment 和 ESPN Technology (DE&E Technology) 為 Disney 的兩個媒體業務部門提供技術骨幹和產品開發，同時幫助公司處於創新尖端，使公司能夠不斷利用技術增強故事講述和創造力，同時為其業務提供可擴展性、靈活性和效率

關於 The Walt Disney Company:

Walt Disney Company 連同其子公司和聯營公司，是領先的多元化國際家庭娛樂和媒體企業，其業務主要涉及三個範疇：Disney Entertainment、ESPN 及 Disney Experiences。Disney 在 1920 年代的起步之初，只是一間卡通工作室，至今已成為娛樂界的翹楚，並昂然堅守傳承，繼續為家庭中每位成員創造世界一流的故事與體驗。Disney 的故事、人物與體驗傳遍世界每個角落，深入人心。我們在 40 多個國家/地區營運業務，僱員及演藝人員攜手協力，創造全球和當地人們都珍愛的娛樂體驗。

這個職位隸屬於 Disney Streaming Technology LLC，其所屬的業務部門是 Disney Entertainment & ESPN Technology。

Disney Streaming Technology LLC 是提供平等就業機會的僱主。求職者都會獲得聘僱考量的機會，不分種族、宗教、膚色、生理性別、性傾向、社會性別、性別認同、性別表達、原國籍、血統、年齡、婚姻狀態、軍人或退伍軍人身份、醫療狀況、遺傳資訊或殘疾狀況、或者聯邦、州級或地方法律所禁止的其他任何基本特徵。Disney 提倡讓所有人的想法和決策都有助我們發展、創新、創造最好故事的商業環境，並與瞬息萬變的世界息息相關。

就業申請的殘疾便利安排

The Walt Disney Company 及其聯營公司是推動平等就業機會的僱主，歡迎所有求職者，包括殘疾人士及殘疾退伍軍人。如你是殘疾人士，並需要合理便利安排以搜尋職位空缺或申請職位，請將要求發送至Candidate.Accommodations@Disney.com。本電郵地址不擬用於一般僱傭查詢或通訊。我們只會回應與網上申請系統殘疾人士無障礙功能相關的要求。

遇到技術問題？查看常見問題以尋求協助。

招聘流程

  • 您的故事從哪裡開始？

    探索 Disney 職位空缺和 The Life at Disney 網誌，了解華特迪士尼公司有待發掘的所有精彩機會。

  • 迪士尼的故事裏，有你更精彩成就迪士尼故事

    有許多不同品牌和業務可供探索。當您找到適合您的機會後，請填寫您的申請，進行下一步。

  • 下一章

    申請後，您將收到一封電子郵件，讓您可存取應徵者控制面板。建立您的登入資料，並確保經常檢視您的控制面板，以查看申請進度。

探索此地點 紐約州紐約市

紐約市擁有全球知名的天際線，有 840 萬人稱之為家，她洋溢著多元化和興奮，從標誌性的景點到等待被發掘的隱世瑰寶，應有盡有。

相關工作

我們的文化

相關內容

  • 行政領導

    我們的高級主管為公司的日常營運帶來了豐富經驗、遠見思維和對卓越、創意和創新的共同承諾。

    了解更多 

  • 多元、公平與包容

    在 Disney，我們致力於創造一個更美好的世界。整個世界充滿歸屬感，讓每人都覺得備受重視、傾聽和理解。整個世界滿載希望和承諾。

    了解更多 

登記收取職缺通知

即時收到最新的工作機會的資訊。

關注我們的職位

星號表示必填欄位。

興趣要求從選項列表中選擇工作類別。從選項列表中選擇工作地點。最後，點擊「添加 (Add)」以建立你的職缺通知。

一經建立帳戶，即代表本人同意使用條款，並確認已閱讀私隱政策。

一經點擊「提交」，即同意我們的使用條款，並確認已閱讀我們的私隱政策。如果本人選擇接收營銷訊息或電子通訊，本人可以隨時撤回對這些營銷訊息的同意。

一經點擊「提交」，即同意我們的使用條款，並確認已閱讀私隱政策、Cookie 政策及歐盟私隱權內容。

我們如何使用您的個人資料以及您的權利：

  1. 你的個人資料由 The Walt Disney Company Limited 控制，公司地址為：3 Queen Caroline Street, London, W6 9PE, United Kingdom。
  2. 當你遊覽 Disney、在 Disney 購物或使用任何 Disney 產品、服務或流動應用程式，The Walt Disney Company Family of Companies 亦可能使用你的資料，以向你提供此等服務、度身定制你的體驗，並向你發送有關服務的最新消息及通訊資料。
  3. 你擁有多項權利，包括有權要求存取、更改或移除你的個人資料，或更改你的營銷偏好設定（包括隨時撤回同意）。請參閱我們的私隱政策，以進一步了解如何管理你的營銷偏好設定或刪除你的帳戶。
  4. 如欲聯絡我們的資料保護專員，可發送電郵至：dataprotection@disney.co.uk。
  5. 你有權向英國資訊專員的辦事處投訴：https://ico.org.uk/。
  6. 有關 Disney 資料收集和使用方式的更多資料，請見 Disney 的私隱政策。

點擊「提交」，即表示你同意我們的使用條款，並確認你已經閱讀我們的私隱政策和收集聲明。

如要進一步了解我們的一般資料收集、用途及做法，包括如何管理你的喜好設定，請參閱我們的私隱政策。本人已閱讀和同意使用條款。