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AI/ML Research Engineer - Camera & Photos

Apple

AI/ML Research Engineer - Camera & Photos

Apple

Cupertino, CA

·

On-site

·

Full-time

·

3d ago

Apple devices capture and edit trillions of photos and videos every year. A new team within Camera and Photos Software is being formed to push the boundaries of how visual intelligence is built, evaluated, and delivered across Apple's imaging stack. You'll work with modern deep learning, from vision-language models and generative approaches to robust evaluation methods, owning models end-to-end from research through handoff. This is a founding role for a hands-on engineer who wants to shape a team's technical direction and ship ML that impacts billions of users.
Join us in building the next generation of visual intelligence at Apple, from perception to generation, research to product, at a scale few teams in the world can match.

Description:

As a machine learning research engineer on this team, you will work across the full ML lifecycle, from problem formulation and data strategy to model development and rigorous evaluation. You'll build and adapt deep networks including vision-language models, generative models, and learned perceptual representations to solve challenging problems in Apple's camera and photos ecosystem.

This is a cross-functional role. You will collaborate with teams across imaging algorithms, ML frameworks, and system performance to define problems, align on metrics, and ship solutions that work on real-world content at Apple scale.","responsibilities":"Research and develop ML models for visual understanding, generation, and evaluation, spanning architectures such as vision-language models, diffusion models, and learned perceptual representations.

Own data strategy end-to-end: define data needs, drive collection and labeling, and build the datasets that make models succeed.

Prototype rapidly, iterate on ideas, and translate successful research into reliable code, tools, and pipelines.

Explore agentic and automated workflows that accelerate model development, evaluation, and integration.

Collaborate cross-functionally with imaging, frameworks, and product teams to define problems and ship solutions.

Improve model robustness by identifying failure modes, designing targeted evaluations, and closing gaps in real-world performance.

Preferred Qualifications:

Experience with vision-language models, multi-modal foundation models, or diffusion-based generative models, including fine-tuning, evaluation, or adaptation for real-world tasks.

Familiarity with classical computer vision, image processing, or camera/imaging pipelines.

Experience with perceptual quality modeling or learned evaluation metrics is a plus.

Experience working with large-scale image or video datasets and performance-sensitive systems.

Interest in agentic AI systems and automated ML workflows.

Curious, inventive, and energized by hard, ambiguous problems.

Minimum Qualifications:

Strong fundamentals in machine learning and deep learning.

Demonstrated ability to develop and evaluate ML models for vision problems, whether in computer vision, computational imaging, generative modeling, or multimodal learning.

Hands-on experience training or fine-tuning deep networks, including data preparation, experimentation, and rigorous evaluation.

Proficiency in Python and experience with Py Torch or similar deep learning frameworks.

Master's or Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, 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 $147,400 and $272,100, 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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About Apple

Apple

Apple

Public

A technology company that designs, manufactures, and markets consumer electronics, personal computers, and software.

10,001+

Employees

Cupertino

Headquarters

$3.5T

Valuation

Reviews

4.0

10 reviews

Work Life Balance

4.0

Compensation

4.2

Culture

3.8

Career

3.5

Management

3.2

75%

Recommend to a Friend

Pros

Great coworkers and people

Excellent benefits and perks

Fast-paced and engaging work environment

Cons

High expectations and pressure

Management quality varies

Limited career progression opportunities

Salary Ranges

17,968 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Principal/L7

Senior/L5

Staff/L6

Junior/L3 · Data Scientist ICT2

0 reports

$121,979

total / year

Base

-

Stock

-

Bonus

-

$103,682

$140,276

Interview Experience

5 interviews

Difficulty

3.4

/ 5

Duration

28-42 weeks

Offer Rate

20%

Experience

Positive 20%

Neutral 40%

Negative 40%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Behavioral Interview

5

Onsite/Virtual Interviews

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Culture Fit