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Senior Machine Learning Scientist - Ad Campaign Optimization (Recommendations)
Cupertino, CA
·
On-site
·
Full-time
·
2w ago
Compensation
$181,100 - $318,400
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Relocation Assistance
•Healthcare
•401k
•Equity
•Learning
Required Skills
Machine Learning
Recommendation Systems
Python
Java
Experimental Design
Statistics
At Apple, we strive every day to create products that enrich people's lives. Apple Ads enables users worldwide to discover new content seamlessly while empowering publishers and developers to promote and monetize their work. Our technology powers advertising in the App Store and Apple News, delivering highly-performant, privacy-first solutions that set new industry standards.
We are seeking a self-motivated individual that will build out the next generation of our ads platforms and ensure that Apple provides the most relevant and high quality ads experience while maintaining a healthy marketplace. You will develop models and systems that improve our platform across the board, develop production code to generate high quality ad recommendations and 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 will also 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. You have, 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 will 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 or recommendation systems and AI agents, ideally within the ads space. You will have an excellent understanding of scalable architectures and thrive working in Agile environments. The ability to be a great teammate under tight deadline constraints is key to success.
Description:
In this role, you will design and build scalable solutions that enable advertisers and internal GTM teams to improve their outcomes on the Apple Ads. You will have the opportunity to build the next generation solutions for providing personalized recommendations that enable driving optimal campaign performance and advertiser experience. You will work with a variety of cross functional business partners to set strategy and bring end-to-end solutions that scale as we grown. You will have the opportunity to apply your ability to move the state of the art techniques in a fast growing business that positively impacts publishers, developers and Apple users at global scale.
Preferred Qualifications:
3+ years of experience building machine learning and recommendation system capabilities across many different product areas at scale
Experience in recommendation systems, personalization or AI agents is highly preferred
MS or PhD, or equivalent experience, in n Machine Learning, Statistics, Optimization or related field with experience building production systems with experience building production systems or have equivalent experience working with large data science / machine learning projects in industry
Minimum Qualifications:
5+ years of experience in machine learning, recommendation systems and LLM based agentic systems
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 knowledge of design of experiments, online experimentation approaches, preferably at scale
Ability to formulate and advocate for R&D objectives and results to cross-functional team members including executive business leadership and product management
Experience contributing and/or reviewing research for top conferences and publications
Deep fluency in Java or Python:
Experience with Spark, Hadoop or other distributed frameworks
BS, or equivalent experience, in Machine Learning, Statistics, Optimization or related field with experience building production systems
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 .
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.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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About Apple

Apple
PublicA technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.
10,001+
Employees
Cupertino
Headquarters
$3.5T
Valuation
Reviews
4.0
10 reviews
Work Life Balance
4.0
Compensation
4.2
Culture
3.8
Career
3.5
Management
3.2
75%
Recommend to a Friend
Pros
Great coworkers and people
Excellent benefits and perks
Fast-paced and engaging work environment
Cons
High expectations and pressure
Management quality varies
Limited career progression opportunities
Salary Ranges
17,968 data points
Junior/L3
L2
L3
L4
L5
L6
M3
M4
M5
M6
Principal/L7
Senior/L5
Staff/L6
Junior/L3 · Data Scientist ICT2
0 reports
$121,979
total / year
Base
-
Stock
-
Bonus
-
$103,682
$140,276
Interview Experience
5 interviews
Difficulty
3.4
/ 5
Duration
28-42 weeks
Offer Rate
20%
Experience
Positive 20%
Neutral 40%
Negative 40%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Behavioral Interview
5
Onsite/Virtual Interviews
6
Team Matching
7
Offer
Common Questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Culture Fit
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