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职位Apple

Senior Visual Generative Modeling Research Engineer (Apple Intelligence), SIML - ISE

Apple

Senior Visual Generative Modeling Research Engineer (Apple Intelligence), SIML - ISE

Apple

Cupertino, CA

·

On-site

·

Full-time

·

3d ago

The System Intelligence and Machine Learning (SIML) organization is seeking visual generative modeling research engineers to build the next generation of experiences and capabilities in Apple Intelligence. This is an opportunity to join a dedicated core group in the Intelligent System Experience organization at Apple, which built the foundational image generation technologies behind Image Playground, Genmoji, Image Wand and Photos Clean Up experiences. Join us as we transform the way billions of users express themselves, create and communicate, on Apple platforms!

Description

We are looking for a Sr Research Engineer with a proven track record in applied ML research. This role will include training large scale conditional generative models in the visual domain on distributed backends, deployment of neural architectures such as transformers efficiently, and learning adaptive policies that can be personalized to the user in a privacy preserving manner. Ensuring quality in the field, with an emphasis on fairness and model robustness would constitute an important part of the role.

You will be interacting very closely with a variety of ML researchers, software engineers, hardware & design teams cross functionally. The primary responsibilities associated with this position range from algorithm design and implementation, ability to integrate research into production frameworks, and collaborating closely with product teams before and after feature launch.","responsibilities":"Designing, implementing, and deploying state-of-the-art conditional visual generative models.

Directly interacting with all cross-functional stakeholders to gather product requirements and translating these into actionable plans for ML research and development.

Effectively communicating results and insights gained to partners and senior leaders, providing clear and actionable recommendations.

Staying abreast with the latest trends, technologies, and best practices in machine learning, visual generative models, multi-modal foundation models, computer vision and natural language understanding.

Actively contributing to ML community at the company by disseminating research ideas and results, enhancing shared infrastructure, and mentoring fellow practitioners.

Preferred Qualifications

Strong background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience.

Experience in addressing challenges associated with the transition of a prototype into a shipping product.

Demonstrated leadership in applied research and development.

Excellent written and verbal communications skills, be comfortable presenting research to large audiences, and have the ability to work hands-on in multi-functional teams.

Minimum Qualifications

Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience.

Hands on experience training larges scale visual generative models (e.g. diffusion models) and/or adapting pre-trained models for downstream tasks.

Strong programing skills in Python or C++.

Proficiency in deep learning libraries like Pytorch or equivalent deep learning frameworks.

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 $147,400 and $220,900, 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