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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 Senior Machine Learning Engineer, 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.
Description
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.
You will collaborate with outstanding Search and AI engineers on large scale machine learning to improve Query Understanding, Retrieval, and Ranking, developing fundamental building blocks needed for AI powered experiences such as fine-tuning and reinforcement learning. This involves pushing the boundaries on document retrieval and ranking, developing sophisticated machine learning models, using embeddings and deep learning to understand the quality of matches. It also includes online learning to react quickly to change and natural language processing to understand queries. You will work with petabytes of data and combine information from multiple structured and unstructured sources to provide the best results and accurate answers to satisfy users' information-seeking needs.
Responsibilities
12+ 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
Minimum 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
Preferred Qualifications
MS or Ph.D in AI, Machine Learning, Information Retrieval, Computer Science, Statistics, or a related field
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