Jobs
Compensation
$171,600 - $258,100
Benefits & Perks
•Healthcare
•401(k)
•Equity
•Learning Budget
•Healthcare
•401k
•Equity
•Learning
Required Skills
Python
PyTorch
Machine Learning
Computer Vision
The System Intelligence Machine Learning (SIML) organization is looking for Research Engineers with a strong foundation in Machine Learning and Computer Vision to develop the next generation of multi-modal Human Sensing technologies. You will be part of a fast-paced, impact-driven Applied Research organization building foundation models for facial and full-body perception, and working on cutting-edge machine learning that is at the heart of the most loved features on Apple platforms including Apple Intelligence, Camera, Photos, Visual Intelligence, etc. These innovations form the foundation of the seamless, intelligent experiences our users enjoy every day!
Description:
As a Machine Learning Research Engineer, you will be responsible for designing and developing cutting-edge AI/ML models for Human Sensing, with a focus on building robust cross-domain identity recognition systems. Multi-modal Human Sensing is a foundational capability that powers intelligent experiences based on key human traits such as identity, expression, clothing, action, gesture, gaze and human-object interaction. Major Apple Intelligence experiences such as personalized Natural Language Search, Memories Creation, as well as personalized Image Generation are powered by our ability to learn robust representations of visual human traits. Efficient real-time visual human sensing powers flagship Photography experiences such as Cinematic mode and Photographic Styles, communication experiences such as Center Stage, and paves the way for more natural human-device interactions, e.g., with the Dock Kit framework.
YOUR PRIMARY RESPONSIBILITIES WILL INCLUDE:
Designing, implementing, and deploying state-of-the-art visual recognition systems.
Building foundation models for facial and full-body perception.
Driving data quality excellence through strategic dataset curation, validation, and generation to support world-class model development.
Building tools and frameworks for systematic failure analysis, identifying edge cases, and driving continuous model improvement.
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 to partners and senior leaders, providing clear and actionable recommendations.
Staying current with the latest trends, technologies, and standard methodologies in machine learning, multi-modal foundation models, computer vision and natural language understanding.
Actively contributing to Apple's ML community by disseminating research ideas and results, enhancing shared infrastructure, and mentoring fellow practitioners.
Preferred Qualifications:
Expert-level knowledge of state-of-the-art methods in face recognition or other facial analysis and biometric systems.
Hands-on experience training multi-modal large language models.
Experience with on-device ML, model optimization, or production ML systems.
Minimum Qualifications:
Master's or Ph.D. in Computer Science, Computer Engineering, or related fields; or equivalent professional experience in ML research and development.
Proficient in Python, Py Torch or equivalent deep learning frameworks.
Proven track record of designing and implementing solutions using modern ML architectures.
Background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful software developments.
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 $171,600 and $258,100, 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
PublicA 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
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