招聘
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Relocation Assistance
•Healthcare
•401k
•Equity
•Learning
Required Skills
Java
Scala
Python
SQL
A/B Testing
Machine Learning
Distributed Systems
Statistics
At Apple, we work every day to create products that enrich people's lives. Our Advertising Platforms group makes it possible for people around the world to easily access informative and imaginative content on their devices while helping publishers and developers promote and monetize their work. Today, our technology and services power advertising in Search Ads in the App Store and Apple News. Our platforms are highly-performant, deployed at scale, and setting new standards for enabling effective advertising while protecting user privacy.
Ads ML Experimentation team is looking for a Senior Software Engineer to build the next generation of software platform and systems to advance experimentation that connect millions of global users to content from publishers and developers. Your work will drive the experimentation framework development of machine learned algorithm at scale. You will build sophisticated systems essential in the end-end development of predictive algorithms. You will design and engineer tools for managing AB test experiments, for performing exploratory analysis, and for real-time monitoring of experiment behavior, while preserving privacy of our customers.
Description:
Partner with business leaders and stakeholders to design, implement and evolve the features of a multivariate experimentation platform. Promote experimentation best practices across the organization. Execute on the experimentation roadmap and future integrations with data-driven prioritization. Exercise strong judgment and make thoughtful decisions with ambiguous situations. Striking the right balance between short-term wins vs. long-term success based on various constraints.
You will join and contribute to a culture that emphasizes observability and understandability, reliability, resiliency, simplicity, reusability, extensibility, scalability, velocity and productivity. We are one team, nurturing each other's growth and supporting each other in delivering for our customers and Apple.
Preferred Qualifications:
Degree in Computer Science, Statistics, Applied Math or related field.
5+ years of industry experience designing, building, maintaining, and extending web-scale production systems.
Exposure to AB testing and machine learning methodologies.
Minimum Qualifications:
Skilled at designing and building complex large-scale and distributed software systems in cloud computing environments like AWS
Strong experience in Experimentation frameworks, A/B testing and Machine Learning methodologies
Fluency in programming languages like Java, Scala, Python and SQL
Experience with event stream processing (ESP) technologies like Spark Streaming, Kafka, Flink or equivalent
Experience with backend object stores, automated data pipelines, cloud-native data storage and processing frameworks
Familiarity with data-oriented workflow orchestration frameworks like Airflow, Kubeflow, etc.
Familiarity with statistics and ability to use data analysis techniques to understand data quality, profile system loads, relationships between business metrics, and technical performance
Excellent communication, social and presentation skills
Skilled at operating in a cross-functional organization
Ability to condense complex concepts and analysis into clear and concise takeaways that drive action
Prior experience in advertising industry is a plus
Prior experience with advanced statistical and causal inference is a plus
Curious business attitude with a proven ability to seek projects with a sense of ownership
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
L2
L3
L4
L5
L6
L2 · Business Analyst L2
0 reports
$114,215
total / year
Base
$45,686
Stock
$57,108
Bonus
$11,422
$79,951
$148,480
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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