Machine Learning Engineer - Apple Services Engineering

Details of the offer

Software and Services
Join Apple as a Machine Learning EngineerImagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Come join the Information Intelligence team at Apple. Guide the products and experiences that our core, groundbreaking technologies in search, natural language processing, and artificial intelligence power.
The Apple Services Engineering Video Search Engineering team is looking for an experienced engineer to help build next-generation media search for Apple's groundbreaking devices and platforms, leveraging Machine Learning and Large Language Model (LLM). We are a diverse collective of thinkers and doers, continually reimagining what's possible, to help us all find what we love in new ways. We operate globally in 40+ languages in 170+ countries and power search for Apple TV, Siri, and Spotlight on iOS, macOS, tvOS, and watchOS. We believe privacy is a fundamental human right, and this belief is incorporated into everything we build. Join us to help deliver the next amazing Apple product!
DescriptionAs a member of our fast-paced group, you'll have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for people with excellent applied machine learning experience and solid engineering skills in creating outstanding search services. This role will include the following responsibilities:
Analyzing search retrieval and relevance requirements, issues, and opportunities.Understanding product requirements and translating them into modeling tasks and engineering tasks.Developing techniques and building machine-learned models for search retrieval and ranking problems.Integrating search functions into Apple products, such as TV, Siri, and Spotlight.Building end-to-end production systems including retrieval and ranking to power search.Conducting A/B tests to ensure we objectively measure improvements.Utilizing Spark, Hadoop MapReduce, Hive, and Impala to perform distributed data processing.Minimum Qualifications5+ years of experience in machine learning, deep learning, information retrieval, natural language processing, or data mining.Mastery of two of the following languages: Python, Go, Java, C++.Excellent knowledge and practical skills in major ML and NLP algorithms.Excellent data analytical skills.Experience with large-scale search and machine learning systems is highly desired.Experience with data transformation pipelines and Hadoop, Hive, and/or Impala is a plus.Familiarity with A/B experimentation.Excellent interpersonal and communication skills.Deep understanding of search and information retrieval including indexing, query rewriting, retrieval, and ranking.Experience building search or recommender systems using LLMs.Preferred QualificationsUnderstanding of the Movies/TV-Shows/Sports or equivalent media business.Education & ExperienceAdditional RequirementsAt Apple, base pay is one part of our total compensation package and is determined within a range. The base pay range for this role is between $207,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.Apple employees also have the opportunity to become shareholders 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, discounted products and free services, and reimbursement for certain educational expenses including tuition.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.

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