refresh

트렌딩 기업

트렌딩 기업

채용

채용Apple

AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)

Apple

AIML - Staff Machine Learning Engineer, Answers, Knowledge & Information (AKI)

Apple

Santa Clara, CA

·

On-site

·

Full-time

·

2d ago

The Siri and Information Intelligence team is revolutionizing the way hundreds of millions of people access information on their devices, all while keeping user privacy at the forefront. As an Applied ML team, we're pushing the boundaries of Apple Intelligence, result ranking, and innovative search technologies, all while running a low latency production service. Our work fuels intuitive information experiences across some of Apple's most iconic products, including Siri, Spotlight, Safari, Messages, Lookup, and more. Join us in shaping the future of how the world connects with information!

We are looking for a senior Machine Learning Engineer with a passion for using machine learning to build intelligent search applications. Our team researches and implements novel query understanding, ranking and response generation techniques, machine learning algorithms and models that power amazing Search experiences across Apple products.

Description

In this role you will have the opportunity to develop LLMs and other NLP models for user productivity and improving Siri's ability to answer personal domain questions. Our team owns models which are responsible for answering users' questions using their personal documents with privacy at the forefront, and that integrates with other Siri capabilities to enable powerful user experiences. Role responsibilities include:

  • Contribute to research, design, implementation, and evaluation of models to enhance quality and performance, and to support key functions for Personal Q&A.

  • Implement and extend LLM models with fine-tuning and RLXF methodologies. Develop high quality data pipelines to support these methodologies.

  • Establish target quality metrics and evaluation sets for the team to track and improve. Design novel experiments to validate/refute hypotheses and support team wide decision making.

  • Collaborate with partner teams to define product requirements and priorities, and to explore opportunities for enhancements to the Personal Q&A stack.

  • Develop long-term technical vision for Personal Q&A quality; identify problem areas and integrate solutions as part of a larger roadmap.

Preferred Qualifications

In-depth knowledge and expertise in training, evaluating, and applying Deep learning models, Large Language Models for production systems

Extensive experience in building production ML systems and applications in search, recommendation systems, or information retrieval

Ability to quickly prototype ideas / solutions, and perform critical analysis

Background in: search relevance and ranking, Q&A, personalization, user behavior/response modeling, or data-driven decision-making

Advanced degree (Master's or Ph.D.) in Computer Science, Statistics, or related field, or equivalent industry work experience

Minimum Qualifications

8+ years industry experience in Machine Learning, NLP and applying these techniques at scale

Strong software engineering skills in mainstream programming languages, such as: Python, Go, C/C++

Experience using ML frameworks (py Torch, JAX, Tensor Flow, XGBoost etc.)

Strong communication skills

Bachelors in Computer Science:

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.

총 조회수

0

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