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 redefining how billions of people use their devices to get information. We are an Applied ML team pushing the limits of question answering, assistant response ranking, and search technologies, while also responsible for a production service. We are part of a wider effort to power information across a variety of Apple products – including Siri, Spotlight, Safari, Messages, Lookup, and more.
As a Staff 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
As a member of our fast-paced group, you’ll have the unique and rewarding opportunity to shape upcoming products from Apple. Our team includes a diversity of backgrounds from applied scientists with a focus in NLP to experienced distributed systems engineers. As such, we are looking for candidates with in-depth understanding of machine learning fundamentals, applied machine learning experience, and strong software engineering skills.
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.
As part of our team, you will be leveraging and improving upon the latest deep learning techniques, such as LLM and RAG, in order to understand queries and user intents, rank documents, and find useful answers to users’ questions. Our team is responsible for training, fine-tuning and deploying these models at scale, using the latest advances for online inference optimization. Following is the primary list of responsibilities for an ML engineer in the team:
Minimum Qualifications
MS in Computer Science or related field
10+ years of work experience in machine learning, deep learning or related field
10+ 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
PhD in Computer Science, Artificial Intelligence, Machine Learning, Information Retrieval, Data Science or related field
Strong industry background and experience in search and related technologies (LLMs, Machine Learning, NLP, Information Retrieval, Question Answering)
Strong and validated experience of ML development and production systems
Experience working with foundation models and LLMs
