<h3>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.</h3>A few reasons why we think you’d love working for Disney Entertainment & ESPN Technology:<ol><li>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.</li><li>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.</li><li>Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.</li></ol><h3>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.</h3><h3>Responsibilities:</h3><ol><li>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.</li><li>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.</li><li>Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards.</li><li>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.</li><li>Experience loading and querying cloud-hosted databases.</li><li>Building streaming data pipelines using Kafka, Spark, or Flink.</li></ol><h3>Basic Qualifications:</h3><ol><li>3+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience.</li><li>Bachelor’s degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.</li><li>3+ years writing production-level, scalable code (e.g. Python, Scala).</li><li>3+ years of experience developing algorithms for deployment to production systems.</li><li>In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings.</li><li>Experience deploying and maintaining pipelines (AWS, Docker, Airflow) and in engineering big-data solutions using technologies like Databricks, S3, and Spark.</li><li>Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate.</li><li>Strong written and verbal communication skills.</li></ol><h3>Preferred Qualifications:</h3><ol><li>MS or PhD in statistics, math, computer science, or related quantitative field.</li><li>Production experience with developing content recommendation algorithms at scale.</li><li>Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment.</li><li>Familiar with metadata management, data lineage, and principles of data governance.</li></ol>#DISNEYTECH <h3>Compensation:</h3>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.
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Job Posting Title:Sr Machine Learning EngineerReq ID:10100853Job Description:Department/Group Overview:Disney Entertainment & ESPN TechnologyOn 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<ul><li>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.</li><li>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.</li><li>Innovation: We develop and execute groundbreaking products and techniques that shape industry norms and enhance how audiences experience sports, entertainment & news.</li></ul>Job Summary:<div>The Search Machine Learning (ML) team powers the ML aspects of search engines for Disney+ and Hulu platforms, in a highly collaborative environment. ML-based services are embedded inside the entire life cycle of search journey, from query understanding, semantic retrieval, and engagement-based re-ranking of contents. Working closely with our search core counterpart team and product stakeholders, we are constantly testing new ideas, and bringing the proven ones into fruition, through experimentation.</div>In this role, you will be responsible for maintaining and iterating on the training jobs and inference endpoints for our ML micro-services that power Hulu Search Engine. In this role, you will be partnering closely with data engineering/data science leads, and work together towards constant iterations on our state-of-the-art ML micro-services.Responsibilities and Duties of the Role:<ul><li>Design and develop batch training jobs (both on CPU and GPU) and inference endpoints on both on-prem and cloud resources.</li><li>Ensure healthy training configurations for tensorflow/pytorch training jobs, and serving layers (through both gRPC and REST).</li><li>Helping data scientists by packaging their model into well-known frameworks such as pyTorch, lightGBM, and ready for production.</li><li>Set up MLOps workflows (both deployment and maintenance) using the state-of-the-art MLOps tools.</li><li>Ability to work on multi-faceted projects with engineers from diverse backgrounds, heterogenous skills and across teams.</li><li>Work in an Agile environment that focuses on collaboration and teamwork</li></ul>Required Education, Experience/Skills/Training:Basic Qualifications <ul><li>5+ years of software experience, with 3+ years of relevant ML and software experience</li><li>Knowledge of the Python/Java ecosystem.</li><li>Knowledge of either pyTorch or Tensorflow frameworks.</li><li>Experience deploying and running services in AWS.</li><li>Expertise with ML pipelines, algorithms, and statistical methods</li><li>Hands-on experience with customer-facing production ML models</li><li>Follow MLOps best practices</li></ul>Preferred Qualifications <ul><li>Experience with ML platforms, such as AWS SageMaker, Google Vertex AI, or any other ML platform.</li><li>Experience in adopting open source ML packages into the MLOps lifecycle.</li><li>Excellent communication and people engagement skills, and mentor colleagues on best practices and technical concepts of building large scale solutions</li></ul>Required Education <ul><li>Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.</li></ul>The hiring range for this position in Los Angeles, CA, Santa Monica, CA, and Bristol, CT is $136,100.00 - $182,400.00 per year, in Seattle, WA and New York, NY is $142,600.00 - $191,100.00 per year and in San Francisco, CA $149,000.00 - $199,800.00 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.Job Posting Segment:Product & Data EngineeringJob Posting Primary Business:PDE - Engagement Experiences & PlatformsPrimary Job Posting Category:Machine LearningEmployment Type:Full timePrimary City, State, Region, Postal Code:Santa Monica, CA, USAAlternate City, State, Region, Postal Code:USA - CA - Market St, USA - CT - ESPN Building 13, USA - NY - 1211 Avenue of the Americas, USA - WA - 925 4th AveDate Posted:2024-09-27
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Machine Learning Engineer Jobs in Santa Monica, CA

Lead Machine Learning EngineerNovember 16, 2024

Machine Learning Engineer IiNovember 14, 2024

Lead Machine Learning EngineerNovember 13, 2024

Lead Machine Learning EngineerNovember 13, 2024

Sr Machine Learning EngineerNovember 13, 2024

Sr Machine Learning EngineerOctober 29, 2024

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Lead Machine Learning Engineer
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Sr Machine Learning Engineer
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