Department/Group Overview: Disney Entertainment & ESPN Technology 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.Job Summary: 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.
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. 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: Design and develop batch training jobs (both on CPU and GPU) and inference endpoints on both on-prem and cloud resources.Ensure healthy training configurations for tensorflow/pytorch training jobs, and serving layers (through both gRPC and REST).Helping data scientists by packaging their model into well-known frameworks such as pyTorch, lightGBM, and ready for production.Set up MLOps workflows (both deployment and maintenance) using the state-of-the-art MLOps tools.Ability to work on multi-faceted projects with engineers from diverse backgrounds, heterogenous skills and across teams.Work in an Agile environment that focuses on collaboration and teamwork.Required Education, Experience/Skills/Training: Basic Qualifications: 5+ years of software experience, with 3+ years of relevant ML and software experience.Knowledge of the Python/Java ecosystem.Knowledge of either pyTorch or Tensorflow frameworks.Experience deploying and running services in AWS.Expertise with ML pipelines, algorithms, and statistical methods.Hands-on experience with customer-facing production ML models.Follow MLOps best practices.Preferred Qualifications: Experience with ML platforms, such as AWS SageMaker, Google Vertex AI, or any other ML platform.Experience in adopting open source ML packages into the MLOps lifecycle.Excellent communication and people engagement skills, and mentor colleagues on best practices and technical concepts of building large scale solutions.Required Education: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field.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.
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