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职位Apple

Staff Data Science Engineer, Siri Runtime Systems and Interaction

Apple

Staff Data Science Engineer, Siri Runtime Systems and Interaction

Apple

Cupertino, CA

·

On-site

·

Full-time

·

2d ago

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

Do you want to make Siri and Apple products more intelligent for our users? The Siri Attention and Invocation team is the front door to Siri. We make sure all our Apple costumers can invoke Siri how and when they want to.

Description

As part of Siri Attention and Invocation team, we collaborate to deliver the next revolution in human-computer interaction, to inspire and create groundbreaking technology for large scale systems, spoken language, big data, and artificial intelligence, to overcome real-world challenges through innovation and user-centered systems that focus on improving the daily life of millions of our customers.

We are seeking an exceptional Staff Data Science Engineer to join our team and drive strategic data science initiatives across the organization.","responsibilities":"In this role, you will lead the development of advanced machine learning solutions, mentor junior team members, and shape our data science roadmap.

Key Responsibilities:

Lead complex data science projects from conception through production development

Establish best practices for model validation, and monitoring

Drive technical decisions and architecture for ML/AI initiatives

Identify high-impact opportunities where data science can drive business value

Collaborate with product, engineering, and business stakeholders to define requirements

Stay current with emerging technologies and methodologies in data science and ML

Contribute to the company's technical vision and data strategy

Preferred Qualifications

Proficiency with cloud platforms (AWS, GCP, or Azure)

Experience with ML frameworks (Tensor Flow, Py Torch, scikit-learn)

Familiar with workflow orchestrators like Airflow or Kubeflow

Experience deploying models to production environments

Minimum Qualifications

Education: MS or PhD in Computer Science, Statistics, Mathematics, or related field (or equivalent experience)

Experience: 5+ years in data science, machine learning, or related fields

Technical Skills:

Expert proficiency in Python and/or R

Deep understanding of machine learning algorithms and statistical methods

Strong SQL skills and experience with big data technologies (Spark, Hadoop, etc.)

Leadership: Proven track record of leading technical projects and mentoring teams

Communication: Excellent ability to explain complex technical concepts to non-technical stakeholders

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