Lead Machine Learning Engineer
工作概要:
Disney Entertainment & ESPN Technology
On any given day at Disney Entertainment & ESPN Technology, we are 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 is 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 would love working for Disney Entertainment & ESPN Technology
- Building the future of Disney’s media business: DE&E (Disney Entertainment & ESPN) 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.
The vision of the Machine Learning (ML) Engineering team at Disney is to drive and enable ML usage across several domains in heterogeneous language environments and at all stages of a project’s life cycle, including ad-hoc exploration, preparing training data, model development, and robust production deployment. The team is invested in continual innovation on the ML infrastructure itself to carefully orchestrate a continuous cycle of learning, inference, and observation while also maintaining high system availability and reliability. We seek to maximize the positive business impact of all ML at Disney streaming by supporting key product functions like personalization and recommendation, fraud and abuse prevention, capacity planning, subscriber growth and lifecycle intelligence, and so on.
In this role You will be expected to lead recommendation and personalization algorithm research, development, implementation, and optimization for product areas, and work on event and context processors to federate data, infrastructure and tooling to enable event-driven ML pipelines. You will own and expand part of our central feature store that powers ML use cases in domains like recommendations, search and fraud. You will work on cross-functional projects and push the envelope on data and ML infrastructure.
What You Will Do
- Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to deploy and develop 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
What You Will Bring
Basic Qualifications
- 7+ years of relevant experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience
- 7+ years of experience writing production-level, scalable code (e.g. Python, Scala)
- 5+ 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
- 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
- Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate
- Familiar with metadata management, data lineage, and principles of data governance
- Experience loading and querying cloud-hosted databases
- Building streaming data pipelines using Kafka, Spark, or Flink
- Experience with: AWS, Docker, Airflow, Databricks
Required Education
- Bachelor’s Degree in Computer Science, Mathematics, Statistics, or related quantitative field or comparable field of study, and/or equivalent work experience.
#DISNEYTECH
The hiring range for this position in Santa Monica, California is $167,700- $224,900 per year and in San Francisco, California is $183,700- $246,400 per year. The hiring range for this position in New York and Seattle, Washington is $175,800 - $235,700 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.
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。
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相關工作
- Senior Site Reliability Engineer Disney Entertainment & ESPN Technology 10094556 西雅圖, 华盛顿州 / 布里斯托尔, 康乃狄克州 / 纽约, 纽约州 申請
- Lead Software Engineer Disney Entertainment & ESPN Technology 10105907 纽约, 纽约州 / 布里斯托尔, 康乃狄克州 / 伯班克, 加利福尼亚州 / 格倫代爾, 加利福尼亚州 / 旧金山, 加利福尼亚州 / 西雅圖, 华盛顿州 申請
- Sr QA Analyst Disney Entertainment & ESPN Technology 10106851 纽约, 纽约州 申請
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