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职位Apple

Proactive Intelligence, Applied Research Scientist - Agentic Systems and Generative Modeling

Apple

Proactive Intelligence, Applied Research Scientist - Agentic Systems and Generative Modeling

Apple

Cupertino, CA

·

On-site

·

Full-time

·

1d ago

AI represents a big opportunity to elevate Apple's products and experiences for billions of people globally. We are looking for Applied Research Scientists with a background and interest in Agentic Systems. You will be leveraging state-of-the-art Generative models to ship extraordinary products, services, and customer experiences for the i Phone, Mac, Apple Watch, i Pad and more. The mission of Proactive Intelligence is to improve Apple platforms by better understanding, anticipating and adapting to user behavior by using machine learning to build phenomenal features that are built right into Apple platforms. Our team provides an opportunity to be part of an incredible research and engineering organization within Apple. The ideal candidate for this role will have industry experience working on a range of modeling problems, including Sequential Decision Making, Reinforcement Learning, Autonomous Systems, Learning from Human Preferences and Training Large Language Models (LLMs). Working knowledge of large-scale data processing especially with structured data, probabilistic modeling and statistics will broaden your role and effectiveness in this position.

Description

As an Applied Research Scientist on our team, you will design and implement ML algorithms that process data in different Apple products. You will train Generative AI models and Agentic systems using deep reinforcement learning to solve hard problems. Where necessary, you will also work on integrating ML/RL frameworks into our products to train large-scale agents and leverage cloud services to enable scalable and distributed training/simulation of agent behaviors. You will communicate advanced ideas to a focused team of researchers in the spirit of developing innovative tools and metrics that change the way we look at problems. You will work closely with other cross-functional teams to align messaging, contribute to roadmaps and contribute software back into different repos for proper integration with core systems. You will write clean, maintainable and production code with appropriate documentation and tests. You will contribute to architecture decisions, design reviews and peer code reviews!

Preferred Qualifications

Familiarity with researching current ML literature and math including optimization methods and modeling techniques

Passionate about building extraordinary autonomous systems with Generative AI

Creative, collaborative and project focused with an ability to work hands-on in multi-functional teams

Proficiency in using ML toolkits such as Py Torch, Tensor Flow, Sk Learn etc.

Minimum Qualifications

Strong programming skills in Python and/or C++ with 3+ years of experience in using these languages for machine learning (ML) modeling and applied research

M.S. or PhD in Computer Science, or a related fields such as Electrical Engineering, Robotics, Statistics, Applied Mathematics or equivalent experience. A minimum of 3 years of experience in applied ML and/or product development.

Fundamental knowledge of ML concepts and hands-on experience in building deep-learning systems

Strong software engineering skills to create scalable and robust infrastructure for machine-learning data, modeling and evaluation systems

Proven ability to train and debug machine-learning systems: defining metrics and datasets, performing error analysis and training models in a modern ML framework

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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关于Apple

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+

员工数

Cupertino

总部位置

$3.5T

企业估值

评价

3.9

10条评价

工作生活平衡

2.5

薪酬

4.2

企业文化

3.8

职业发展

3.5

管理层

3.2

72%

推荐给朋友

优点

Great benefits and compensation

Talented colleagues and supportive teams

Learning opportunities and mentorship

缺点

Work-life balance challenges

High stress and pressure

Fast-paced environment

薪资范围

11,365个数据点

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0份报告

$121,979

年薪总额

基本工资

-

股票

-

奖金

-

$103,682

$140,276

面试经验

3次面试

难度

3.3

/ 5

时长

28-42周

录用率

33%

体验

正面 33%

中性 0%

负面 67%

面试流程

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience