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Senior Machine Learning Engineer - Ads Predictions

Apple

Senior Machine Learning Engineer - Ads Predictions

Apple

Cupertino, CA

·

On-site

·

Full-time

·

3w ago

필수 스킬

PyTorch

TensorFlow

Machine Learning

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!

Description:

We're is looking for a highly skilled and motivated Machine Learning Engineer to join our Predictions group. We build the core machine learning models that power ad predictions and monetization across Apple's App Store and News platforms. The ideal candidate will bring deep expertise in machine learning, information retrieval, and large-scale modeling, and will thrive in a fast-paced, privacy-first environment.

You'll work at the intersection of applied ML, deep learning, and retrieval systems-developing models that predict user interaction, optimize marketplace outcomes, and scale across billions of queries. You'll also explore and operationalize emerging techniques in Large Language Models (LLMs), Reinforcement Learning, and representation learning to advance Apple's ad prediction systems.

","responsibilities":"Design and implement ML models to improve predictions of user interaction, click-through rate (CTR), and conversion rate (CVR)

Develop and optimize retrieval algorithms, leveraging techniques from classical IR and modern deep learning

Contribute to core modeling areas such as deep neural networks, contextual bandits, multi-task learning, and LLM-based ranking signals

Work with large-scale, distributed datasets to identify new signals and improve model accuracy and robustness

Collaborate with cross-functional teams across engineering, infrastructure, and product to scale models to production

Participate in designing and running large-scale experiments to validate new model architectures and learning strategies

Preferred Qualifications:

MS or PhD, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.

Great foundation in information retrieval, including query-document matching, embedding-based ranking, and learning-to-rank algorithms is a plus

Minimum Qualifications:

6+ years of experience applying machine learning and statistical modeling at scale, preferably in ad tech, recommender systems, or web-scale search/retrieval

Deep experience with neural network architectures (e.g., Transformers, DNNs, RNNs) and training pipelines using Tensor Flow, Py Torch

Practical understanding of reinforcement learning, explore/exploit strategies, and bandit-based optimization

Experience working with high-volume data pipelines, A/B testing infrastructure, and performance measurement at scale

Proficient in Python and familiar with SQL, Scala, or Java for production environments

Ability to translate abstract ideas into concrete, high-impact solutions

Bachelor's, or equivalent experience, in Computer Science, Machine Learning, Artificial Intelligence, Information Retrieval, or a related field.

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 $212,000 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.

총 조회수

1

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Apple 소개

Apple

Apple

Public

Apple Inc. is an American multinational technology company headquartered in Cupertino, California, in Silicon Valley, best known for its consumer electronics, software and online services.

10,001+

직원 수

Cupertino

본사 위치

$3.5T

기업 가치

리뷰

3.9

10개 리뷰

워라밸

2.5

보상

4.2

문화

3.8

커리어

3.5

경영진

3.2

72%

친구에게 추천

장점

Great benefits and compensation

Talented colleagues and supportive teams

Learning opportunities and mentorship

단점

Work-life balance challenges

High stress and pressure

Fast-paced environment

연봉 정보

11,365개 데이터

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0개 리포트

$121,979

총 연봉

기본급

-

주식

-

보너스

-

$103,682

$140,276

면접 경험

3개 면접

난이도

3.3

/ 5

소요 기간

28-42주

합격률

33%

경험

긍정 33%

보통 0%

부정 67%

면접 과정

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience