Machine Learning Engineer - Matching, Apple Ads

Machine Learning Engineer - Matching, Apple Ads

Cupertino, California, United States Software and Services

Description

Matching at Ads is a critical component of our Ads funnel and responsible for ensuring that we are retrieving relevant and engaging Ads for our users. We are building the next generation of our retrieval systems to sustain the growth of the business for the future. We are looking for a Machine Learning Engineer that will develop the algorithms for our retrieval  this role you will drive step-change improvements in our outcomes, impact our platform revenue and quality of our ads, and formulate approaches to greenfield product opportunities.

You will own end-to-end the ideation, development, testing and productization of these algorithms. You will work with complex problems in the ads retrieval space, provide solution that adhere to Apple’s privacy principles, review and contribute to state of the art in research, work with a variety of cross functional teams to ensure the feasibility and robustness of delivering new capabilities.

This role will work closely with organizational partners and be expected to present findings across the organization.

Minimum Qualifications

• 4+ years of experience building machine learning capabilities across many different product areas at scale.
• Proven experience in NLP, information retrieval and search.
• Ability to apply and implement research concepts, ultimately in production quality code.
• Experience defining clear, testable research hypotheses, including intended impact on the business.
• Deep understanding of design of experiments, online experimentation approaches, preferably at scale.
• Experience contributing and/or reviewing research for top conferences and publications.
• Master's, or equivalent experience, in NLP, Machine Learning, Statistics, Forecasting, Optimization, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry.

Preferred Qualifications

• 7+ years of experience building machine learning capabilities across many different product areas at scale.
• PhD, or equivalent experience, in NLP, Machine Learning, Deep Learning, Large Language Model, Reinforcement Learning or related field with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry.

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 $147,400 and $272,100, 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 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 .

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