Senior Machine Learning Engineer / Senior Applied Scientist, Search & AI

Apple is where individual imaginations come together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us strengthening each other’s ideas. That happens because every one of us believes that we can make something wonderful and share it with the world, changing lives for the better! Here, you’ll do more than join something — you’ll add something.

The Information Intelligence team is at the forefront of revolutionizing how billions of people interact with their devices to search and find what they are looking for. As a Machine Learning Expert, you play a critical role in developing world-class Search and Q&A experiences for Apple customers with cutting-edge search technologies and large language models.

Our team is responsible for delivering next-generation Search and Question Answering systems across Apple products including Siri, Safari, Spotlight, and more. This is your chance to shape how people get information by leveraging your Search and applied machine learning expertise along with robust software engineering skills.

Minimum Qualifications

8+ years experience in shipping Search and Q&A technologies and ML systems Excellent programming skills in mainstream programming languages such as C++, Python, Scala, and Go Experience delivering tooling and frameworks to evaluate individual components and end-to-end quality Strong analytical skills to systematically identify opportunities to improve search relevance and answer accuracy Strong written and verbal communication with the ability to articulate complex topics Excellent interpersonal skills and teamwork; demonstrated ability to connect and collaborate with others Passion for building phenomenal products and curiosity to learn

Preferred Qualifications

Background in Search Relevance and Ranking, Question Answering systems, Query Understanding, Personalization or Recommendation systems, or data-informed decision-making Hands-on experience in Retrieval Augmented Generation (RAG), including developing, evaluating and enhancing for both retrievers and generative LLMs Experience presenting plans, progress, and results or demos regularly and concisely MS or Ph.D in AI, Machine Learning, Information Retrieval, Computer Science, Statistics, or a related field