Machine Learning Engineer

Apple Inc.
Cupertino, CA, United States
about 1 month ago
Apply on www.themuse.com
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
4 years minimum
Compensation
$150,400.0
Working hours
Regular working hours

Tech stack

Agile Methodology Big Data Information Retrieval Machine Learning Natural Language Processing Reinforcement Learning Deep Learning

Job 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 system.

In 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.

Requirements

You’ve, or will develop a deep understanding of the ad network behavior, and will work with product management and business leadership to prioritize an innovation roadmap across multiple technical domains. You’ll lead the conception, development, and delivery of state of the art capabilities that differentiate our products and are core to our business. You should have experience developing and implementing machine learning algorithms, ideally within the ads space. You’ll have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a good team player under tight deadline constraints is key to success., 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., 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.

Benefits & conditions

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 $150,400 and $277,600, 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

About the company

At Apple, we focus deeply on our customers’ experience. Apple Ads brings this same approach to advertising, helping people find exactly what they’re looking for and helping advertisers grow their businesses! Our technology powers ads and sponsorships across Apple Services, including the App Store, Apple News, and MLS Season Pass.

Everything we do is designed for trust, connection, and impact: We respect user privacy, integrate advertising thoughtfully into the experience, and deliver value for advertisers of all sizes-from small app developers to big, global brands. Because when advertising is done right, it benefits everyone!

You’ll have the opportunity to develop models that improve our platform across the board, write production code to generate recommendations, work closely with business partners to help drive the development of new products as well as perform large scale and complex experiments to understand their effects. You’ll drive strategic outcomes through substantial innovation in multiple fields by leading the development and application of advanced techniques and algorithms to improve our ad network.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.themuse.com
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:28 min

Defining big data and machine learning fundamentals

Ayon Roy · LIVE

2:47 min

Contrasting classical machine learning with deep learning approaches

Adrian Spataru +1 · LIVE

2:36 min

Applying supervised machine learning for practical rule extraction

Katja Träumner

40 sec

Navigating Apple's evolving on-device AI and machine learning stack

Precious Osaro Precious Osaro · World Congress 2026 Europe

2:10 min

Why organizations combine big data and machine learning

Ayon Roy · LIVE

3:14 min

Structuring career paths and localized data architectures

Ulrich Wurstbauer +1 · LIVE

Videos

See all

Related articles

See all