Summary

Posted: Nov 14, 2024

Role Number:200578997

At Apple, new ideas have a way of becoming phenomenal products, services, and customer experiences very quickly! Bring passion and dedication to your job and there's no telling what you could accomplish. Does an engaged, user-focused, and high impact environment catch your attention? Do you like puzzles and determining solutions that are not obvious? Terrific! Consider joining us.

Description

Our Apple News team is seeking a high-energy and self-driven Machine Learning Engineer who will play a central role in the delivery of scalable services. The team uses machine learning to tackle complicated problems in the News domain, including text extraction, named entity recognition, duplicate detection, search and ranking. As a member of our dynamic group, you'll have the rare and rewarding opportunity to craft upcoming products that will delight and encourage millions of Apple's customers every day. Join us to improve the lives of millions of users, and you will: - Design and implement state-of-the-art machine learning models that process text, personalize feeds, and make the impossible possible. - Collect model training data, design model architecture, and train custom or fine tuned models or adapters suited for application features. - Partner with cross-functional teams at the intersection of technology and liberal arts to design and implement end-to-end machine learning enabled features. - Drive application features from concept, model design, development and all the way to delivery. - Join a thriving machine learning community at Apple.

• MS in Machine Learning, Computer Science or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.
• At least 2 years of experience shipping machine learning models in products.
• Strong programming skills in Python, Java, or a related language, and one of the deep learning toolkits such as PyTorch, TensorFlow, or similar.
• Ability to communicate effectively and collaborate with partner teams.
• Committed to encouraging an open and inclusive work environment.

• Ph.D. in Machine Learning, Computer Science, or related field.
• 5 years of experience shipping machine learning models in products.
• Experience with personalized ranking and scoring is a plus.
• Experience with text data and NLP tasks is a plus.
• Experience delivering high quality software at scale is a plus.
• Experience designing user-facing machine learning features with interdisciplinary partners is a plus.

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. Learn more 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.