Sr. Applied Research Scientist

Seattle, Washington, United States Machine Learning and AI Siri helps hundreds of millions of people find the information they are looking for. A critical part of that mission is helping them quickly find and discover local businesses, places of interest, and addresses. Users rely on us for relevant and easy access to local information like finding a favorite or romantic restaurant, business hours, nearby coffee shop addresses, and directions to prominent locations. The Geo domain team is redefining how hundreds of millions of people use their devices to navigate and explore the physical world around them. We are part of a wider effort to power search across a variety of Apple products – including Siri, Spotlight, Safari, Messages, and more. As part of our team, you will be using innovative machine learning techniques and LLMs in order to understand queries, rank documents, and find useful answers to users' questions. We are looking for an experienced applied researcher with hands‑on experience in search and recommendation and deploying powerful machine learning models at scale. You will join a team that combines strong technical skills, product vision, and a love of all things local to bring together the pieces needed to deliver an extraordinary Maps experience in Siri and Spotlight. Description As a member of our high‑impact, iterative environment, 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. We are looking for candidates with both applied machine learning and deep‑learning experience as well as strong engineering skills. Responsibilities Own the entire ML development cycle from opportunity analysis, exploration, and prototyping to data collection, feature engineering, training, evaluation, and deployment in production. Lead the development of machine learning models to improve search quality across retrieval, ranking, reranking, and query understanding. Improve search quality and experience by leveraging techniques such as learning‑to‑rank, embedding models, contrastive learning, multi‑task learning, and reinforcement learning where appropriate. Independently identify high‑impact research directions and drive them to production, translating state‑of‑the‑art findings into measurable improvements in search quality. Partner cross‑functionally with product and design teams to shape the technical roadmap and translate research capabilities into user‑facing impact. Mentor junior engineers and provide technical leadership in architecting ML systems and designing ML models. Understand product requirements, then drive the technical design and model architecture before defining the roadmap. Own the final outcome and learn on every iteration. Minimum Qualifications You have 8+ years of experience in information retrieval, natural language processing, machine learning, or deep learning. You have a deep understanding of machine learning theory, including supervised learning, ranking models, embeddings, representation learning, and evaluation metrics. You have proven ability to apply advanced ML techniques to improve search relevance and retrieval quality at scale. You are comfortable leading experimentation, offline evaluation, and online A/B testing for iterative improvements in search quality. You actively monitor recent research literature — including arXiv, NeurIPS, ICML, ACL, SIGIR, and industry publications — and have a track record of translating findings into practical system improvements. You independently identify high‑impact research directions and drive them forward without requiring top‑down direction. You demonstrate a strong bias toward action, moving fluidly from paper to prototype to production in tight iteration cycles — executing quickly while maintaining quality and rigor. You have excellent interpersonal skills, the ability to work independently as well as part of a team, including cross‑functional collaboration with product and design. You have a Master’s Degree in Computer Science, Machine Learning, or a related field, or equivalent practical experience. Preferred Qualifications PhD in Computer Science, Machine Learning, Information Retrieval, or a related field, or equivalent research experience demonstrated through publications, patents, or significant open‑source contributions. Track record of publishing or presenting at top‑tier research venues such as NeurIPS, ICML, ACL, SIGIR, or equivalent. Experience applying LLMs and generative AI techniques to production search or recommendation systems. Compensation and Benefits At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $201,300 and $302,200, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Accessibility At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong. Learn about accessibility in Apple’s workplace. Learn about reasonable accommodations for job applicants. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant. Apple accepts applications to this posting on an ongoing basis. #J-18808-Ljbffr Apple Inc.