Location: all cities,CA, USA
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.
User Household
The User Household team builds critical User Capabilities that are shared across all experiences on the streaming services: Disney+, Hulu, ESPN+ and Star+. We implement reliable, high-throughput services and pipelines for gathering information about our users, and delivering personalized experiences. We're a fast-paced, dynamic, collaborative and fun team, and are looking for someone who can slot right in and start delivering from day 1.
Job Summary:
As a Lead Machine Learning Engineer, you will collaborate closely with engineers, project managers, and product managers to find the best solution for our viewers. You will drive projects end-to-end: leveraging ML techniques to design the initial solution; finding alignment with partner teams; execution of the necessary code; and overseeing the deployment of code to production. Members of the team look to your code and documentation as examples of excellence. You value good-faith collaboration, driving best practices, and promoting excellence on your team. If this sounds like you, we would love to hear from you!
Responsibilities and Duties of the Role:
Leverage knowledge of ML methods and techniques to design new Machine Learning solutions and drive alignment across engineering and product teams.
Write code to implement new ML features or optimize existing services.
Expertly break down work at the epic level, setting project milestones with reasonable deadlines.
Prioritize work within a project to deliver on the most necessary or urgent requirements.
Anticipate and mitigate risk on projects.
Effectively communicate with stakeholders on project progress.
Actively participate in daily stand-ups and other scrum ceremonies.
Determine the most efficient means to sufficiently test new code: unit tests, integration tests, performance tests, etc.
Set best practices for the team for on-call responsibilities such as deployments, monitoring, and investigating incidents
Use logs, monitoring tools, and work with developers to determine root causes across distributed components.
Perform code reviews for members of the team, bearing a sense of responsibility for approved code.
Coach and mentor teammates in an open, respectful, flexible, empathetic manner. Help onboard new team members.
Required Education, Experience/Skills/Training:
Basic Qualifications
Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience
7+ years of related experience crafting and operating Machine learning services.
1+ years of related experience crafting and operating large-scale, high-availability backend services.
Experience crafting and operating JVM services (such as Java, Scala, Kotlin).
Proven track record of designing and driving consensus on backend architectures.
Deep understanding of and experience using caching technologies (such as Redis, Memcached, EHcache).
Strong grasp of computer science fundamentals (data structures, algorithms, databases, etc).
Strong understanding of design patterns and principles.
Experience with asynchronous programming.
Experience with object-oriented programming patterns.
Experience with functional programming patterns.
Experience using source control systems and CI/CD pipelines (such as git, Github, Jenkins).
Experience with AGILE/Scrum practices.
Skilled at work breakdown and task estimation.
1+ years practicing operational best practices for service maintenance.
Experience deploying and scaling within a cloud infrastructure.
Experience with observability tools for metrics, logging, and monitoring (such as Datadog, Grafana).
Strong communication skills and a desire to share your knowledge with team members and others.