The Video engineering server team is looking for experienced software engineers to build highly scalable, low latency backend services and data systems for the Apple TV app. This service platform is the backbone of the Apple TV app where it is supported, including iOS, tvOS, macOS, visionOS, Roku, Fire TV, and Samsung TV. We handle millions of requests per day from millions of end-users around the world to discover and consume Apple TV+ Originals, Live Sports broadcasts for MLS and MLB leagues, and the vast catalog of content from Apple partners. This is the perfect opportunity for someone who wants to work with highly talented engineers on backend service platforms, data ingestion pipelines, data storage and retrieval systems. If you are interested in the Video domain and is passionate about service reliability and latency optimization, this is the place to be.

DESCRIPTION

We offer an environment where you are an integral part of an innovative, impactful team making a difference. Be ready to make something phenomenal when you come here. Multifaceted, inspiring people and innovative industry-defining technologies are the norm at Apple. The people who work here have reinvented and defined entire industries with our products and services. The same passion for innovation also applies to our business practices - strengthening our dedication to leave the world better than we found it. Join the team to build what’s next!

MINIMUM QUALIFICATIONS

• 5+ years related work experience
• Fluent in Java
• Experienced in Spark
• Built backend services for consumer product
• Built highly scalable micro-services

PREFERRED QUALIFICATIONS

• Knowledge of AI/ML embeddings is preferred
• Experience in video domain preferred
• BS, MS in Computer Science or related domains

• You’ll be working on the video content discovery service platform that powers the Apple TV app. This team is responsible for building recommendation, personalization, catalog query, multi-arm bandit optimization systems. Design and implement services in Java. Perform data analysis using Spark. Candidate should have engineering experience in recommendation systems, personalization. Ideal candidate should also be comfortable with AI/ML concepts like embeddings, reinforcement learning, and integrating AI/ML models into a backend service.