Machine Learning Scientist/Engineer

Summary

Do you want to work on building groundbreaking Machine Learning (ML) technologies and make real world impact? At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The Applied Machine Learning (AML) Data Science team in is a group of innovative ML scientists from diverse disciplines with extensive track records in both academia and industry. ML Scientists on the team work on many high-impact projects, building powerful machine learning models that serve various Apple lines of business and enrich end user experiences. We have the opportunity to do groundbreaking AML work that will shape the industry. As ML Scientists, we develop pioneering machine learning algorithms to enable current and future products and services in various enterprise scenarios!

Description
The ML Scientist will work on solving real world business problems through machine learning and computer vision. You will work to devise models and ml approaches to solve these problems and achieve business KPIs, you will work with large-scale data sets with intensive hand-on code development. In addition, the role requires close partnering with business teams in articulating the research methodologies and results. The role also requires collaboration with engineering teams in integrating and deploying ML models to deliver amazing user experiences. Are you deeply accountable for your work? Your passion for product ownership and track record of product development will prove critical to your success on our team. We are in need of a creative problem solver with deep expertise in machine learning, algorithms, and optimization. You will work with amazing colleagues, brainstorm new ideas, and develop models and algorithms to solve ambitious problems that have a substantial impact.

Minimum Qualifications

• 7+ years of industry experience with a Bachelors Computer Science, engineering or similar foreign degree
• Experienced in one or more of the following ML areas: Computer Vision, NLP, GenAi, AR/VR, Document Intelligence, or similar areas
• Hands on experience in algorithm design, modeling, or quantitative analysis
• Hands on experience in industry experience implementing end-to-end machine learning projects.
• Experience with deep learning framework such as Pytorch, TensorFlow and Keras
• Experience with optimization, approximation algorithms, deep learning, and hands-on implementation of these techniques.

Preferred Qualifications

• An Advance Degree, Ph.D. with 1+ year or Masters with 3+ years of experience in computer science, engineering or similar quantitative field with a focus on machine learning.
• Python is preferred

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 $138,900 and $256,500, 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.