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 leveraging and improving upon the latest deep learning models in order to understand queries, rank documents, and find useful answers to users' questions. We are looking for people with experience in query understanding, machine learning and search ranking powered by sophisticated, high-performance data ingestion pipelines. 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 a world-class Maps experience in Siri and Spotlight.
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 applied machine learning experience and strong engineering skills. The role will have the following responsibilities:
Analyzing search ranking and relevance requirements issues and opportunitiesUtilizing PyTorch and proprietary tools for training deep learning modelsUnderstanding product requirements then translating them into modeling tasks and engineering tasksBuilding machine-learned models for query understanding and search rankingDevelop and maintain large scale indexing and ML data pipelinesMinimum Qualifications Bachelors in Computer Science or equivalent degrees2+ years of experience in natural language processing, machine learning or deep learningProficient in one of the following languages: Python, Go, Java, C++, demonstrating strong background in algorithms and data structuresExcellent interpersonal skills with the ability to work independently as well as in a teamExcellent knowledge and practical skills in major machine learning algorithmsAbility to partner with a variety of cross-functional teams across the companyExcellent communication skills and the ability to collaborate effectivelyMasters Degree in Computer Science or equivalent experience in machine learning or related industryPreferred Qualifications 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 $143,100 and $264,200, 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.Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure 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.
#J-18808-Ljbffr