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Apple
Senior Computer Vision Machine Learning Engineer, Apple Wallet
3 weeks ago• Austin, TX
Viewed on February 1, 2026
Apply on company site
About Us
Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.
- Size: 10000+ employees
- Industry: Technology, Information Technology, Software, Consumer Goods & Services
View Company Profile:
Join a dynamic AI and Machine Learning team focused on protecting millions of users from fraud and securing their identity every day. We operate at the intersection of cutting-edge research and production systems, collaborating across Apple-from other ML teams to Operations to Engineering-with strong leadership support and investment in our mission-critical work.
We value continuous learning, intellectual curiosity, and commitment to excellence while maintaining focus on user Description
You will work on cutting edge computer vision technology in the field of facial recognition and adversarial object detection. You'll contribute to computer vision initiatives that directly protect users from fraud and identity theft, combining applied research with production deployment. This role offers the unique opportunity to see your work from methodology through implementation, with the autonomy to make meaningful technical decisions in a supportive, high-visibility environment.","responsibilities":"Bring computer vision expertise and industry best practices to strengthen team capabilities
Collaborate on advanced computer vision projects, particularly in face recognition and facial expression/spoofing detection
Deliver on roadmap commitments while identifying innovative approaches for model improvement
Mentor early-career engineers, supporting their growth and project success
Partner with cross-functional stakeholders, translating complex technical concepts and instilling trust
Contribute to roadmap planning and execution, bringing industry best practices and novel architectural approaches
Practice thoughtful prioritization and alignment in a high-opportunity environment while embracing Apple's core principles around Preferred Qualifications
Py Torch, Torch Vision or similar expertise in vision-specific libraries and toolkits
Background in security/security engineering, fraud detection, or edge ML deployment
Real-time decisioning systems
Face recognition or biometric security applications
M.S. or PhD in computer science, machine learning, or a related field or equivalent practical experience.
Minimum Qualifications:
Strong foundation in computer vision techniques and machine learning
Proven mentorship experience with demonstrated positive outcomes
Clear technical communication skills across a range of audiences
Strong programming abilities in Python plus at least one additional language
5+ years of relevant experience in Computer Vision Machine Learning
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 .
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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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