Staff Machine Learning Engineer - News, Books, and Stocks Team

In a time where the news and book media landscapes are changing by the day, Apple News and

Apple Books stand as champions of quality content, expert curation, user privacy, and the

judicious use of machine learning.

Our lively and brilliant team consists of client and machine learning engineers who embody

Apple's values. We inspire, teach, and otherwise enable each other to do the best work of our

careers!

Our team's outstanding retention rate speaks to our strong culture of respect for our teammates

as both engineers and people.

Would you like to work on such a team, solving hard problems in machine learning? Terrific!

Please join us for the next generation of these apps!

Description

Our 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

difficult and complicated problems in the news, books, and stocks domains, including text

extraction, named entity recognition, duplicate detection, search, ranking, and much more! 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!

Responsibilities:

Design and implement state-of-the-art AI/ML that processes news, stocks, and books data to drive recommendations, power advanced search, and enable next-generation AI features.

Develop datasets, design model architecture, and prompt, train, or fine-tune models.

Partner with multi-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, and development all the way to delivery.

Lead highly cross-functional software projects.

Mentor junior engineers.

Be part of our thriving machine learning community at Apple.

Preferred Qualifications

Experience in a technical leadership role.

Minimum Qualifications

MS in Machine Learning, Computer Science, or related field. Alternatively, equivalent industry experience to an MS degree is acceptable.

At least 5 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.

Experience designing user-facing machine learning features with interdisciplinary partners.

Experience with recommender systems.

Experience with text-centric AI/ML (LLMs, document classification, search, etc.)

Experience delivering high quality software at scale.

Ability to communicate effectively and collaborate with partner teams.

Commitment to encouraging an open and inclusive work environment.

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 $175,000 and $308,500, 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.