About The Position
The Partner Adoption team, part of the Machine Learning Platform Technologies organization, is the backbone of onboarding applications to Apple’s world-class search and recommendation platform. In this role, you’ll work end-to-end on feature and product design across a broad range of Apple services—including Apple Music, TV+, App Store, Books, Games, Podcasts, Siri, and more. As a key member of the team, you’ll design and build large-scale server-side functionality while also exploring and delivering cutting-edge GenAI applications and features powered by large language models. You’ll partner closely with product, platform, and design teams to bring innovations to life—reaching millions, and even billions, of users worldwide with the reliability and excellence Apple is known for.
Requirements
- Bachelor's degree or higher in Computer Science or related technical field
- 5 year+ industry experience in distributed system and ML Modeling (Search, Recommendation, NLP, Ads, Statistics)
- Experience with high throughput services particularly at supercomputing scale
- Proficient with running applications on Cloud (AWS / Azure or equivalent) using Kubernetes, Docker etc.
- Proficient in building and maintaining systems written in modern languages (eg: Golang, Rust, Python)
Nice To Haves
- Familiar with GenAI Applications and popular agentic framework like Langchain and Langgraph
- Familiar with embedding model and llm serving like Nvidia TensorRT-LLM, vLLLM, DeepSpeed, Nvidia Triton Server etc.
- Familiar with very large scale serving system
Responsibilities
- Develop GenAI search and recommendation application end to end
- Partner with a lot of engineering teams across Apple
- Work end-to-end on feature and product design across a broad range of Apple services
- Design and build large-scale server-side functionality
- Explore and deliver cutting-edge GenAI applications and features powered by large language models
- Partner closely with product, platform, and design teams to bring innovations to life
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What This Job Offers
Job Type
Full-time
Career Level
Senior
