Job Details

Weekly Hours: 40

Role Number: 200623892-0836

Summary

Apple Maps and the thousands of applications it empowers are being used by millions every single day! As a fundamental tool for human activity, Maps technology is evolving and new techniques are emerging.

We are looking for a Machine Learning Engineer to join and help play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of opportunities to build groundbreaking technologies using ML and GenAI at scale to improve the search quality for Apple Maps.

Description

The goal of Maps Search team is to take Apple’s Maps to the next level of intelligence and accuracy using machine learning and artificial intelligence techniques. Engineers and scientists on our team work on a wide spectrum of approaches to improve search experiences on Apple Maps.

This position involves a wide variety of skills and innovation; It is a unique opportunity that sits at the intersection of science and engineering. Ultimately, your work would have a huge impact on millions of users across the globe, so join us and help us in building a world class search team!

Minimum Qualifications

• MS in computer science or equivalent field with 7+ years of industry experience

• Proven record in delivering end-user facing ML driven products

• Strong programming experience in one or more of the following: Java, C++, Python

• Knowledge and experience with one of Tensorflow/Pytorch/Jax frameworks

• Excellent interpersonal and communication skills - working independently and/or in small teams

• Attention to detail, data accuracy and quality of output

Preferred Qualifications

• Ph.D in Computer Science or equivalent field with 7+ years of industry experience

• Expertise and experience in various facets of machine learning and natural language processing, such as classification, feature engineering, information extraction, clustering, semi-supervised learning, topic modeling and ranking

• Practical understanding of the mathematics behind modern machine learning, linear algebra and statistics

• Good knowledge of big data processing, prior experience with Hadoop, Spark, and Hive is highly desired

• Knowledge and prior experience with some deep learning and GenAI frameworks and LLMs

• Prior experience in consumer facing product development and delivery

• Prior experience as a team lead

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 $181,100 and $318,400, 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. (https://www.apple.com/careers/us/benefits.html)

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 seek to promote 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) .