Apple
Sr. Machine Learning Engineering Manager - Maps Search
Apple, Cupertino, California, 95014
Sr. Machine Learning Engineering Manager - Maps Search Cupertino,California,United States Software and Services Apple Maps are being used by millions and powers thousands of applications every single day. Our mission is simple — build the best maps in the world. We are looking for an experienced Senior Engineering Manager to lead an engineering team who are passionate about building best-in-class algorithms and solutions which positively impact Business Search Features on Apple Maps. If you are seeking a role where you can grow and develop an already amazing team of innovative engineers while driving ML and Generative AI solutions at scale, we may have a role for you Description As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging. As a part of our Search Team, you can play huge part in the next revolution of Maps which enable users to find more places and things in more ways As a Senior Manager on our team, you will lead all aspects of our features related to Business Search. You will be responsible for driving definitions and developing, evaluating and deploying multiple search features including large-scale machine learning models, deep-learning and natural language processing solutions which are geared towards improving Search on Maps. Successful managers at Apple are able to own details of projects and long-term vision for the team. They collaborate optimally with partner/product teams to set the goals, expectations, and roadmaps for their teams. As a leader, you will provide technical and career mentorship to your team to ensure their success. This role also requires strong interpersonal skills and the ability to communicate technical details and dependencies to engineering partners, product management teams, and executives across Apple. Minimum Qualifications MS in Computer Science or related field with 10 years of progressive software engineering management experience Experience in leading and developing teams which work in information retrieval domains like search, personalization, recommender systems, assistants, or related areas. Solid understanding of indexing and ranking algorithms Experience with distributed systems and services Experience of building machine learning applications at scale Strong background in execution and delivery of consumer-focused features or products Highly developed interpersonal and communication skills with proven experience partnering with and communicating highly technical concepts and roadmaps to varying levels of partner teams, product management, and executives Key Qualifications Preferred Qualifications PhD preferred Experience evaluating and deploying multiple search features including large-scale machine learning models, deep-learning, and natural language processing solutions Education & Experience Additional Requirements Pay & 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 $219,300 and $378,700, 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 (https://www.apple.com/careers/us/benefits.html) about Apple Benefits.Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. 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. (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) Apple Footer 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 (Opens in a new window) . Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants. United States Department of Labor. Learn more (Opens in a new window) . Apple will consider for employment all qualified applicants with criminal histories in a manner consistent with applicable law. If you’re applying for a position in San Francisco, review the San Francisco Fair Chance Ordinance guidelines (opens in a new window) applicable in your area. Apple participates in the E-Verify program in certain locations as required by law. Learn more about the E-Verify program (Opens in a new window) . Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) . Apple is a drug-free workplace. Reasonable Accommodation and Drug Free Workplace policy Learn more (Opens in a new window) .