Senior Computer Vision Machine Learning Engineer, Apple Wallet
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 privacy and security
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.
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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 privacy, security and the customer 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
Preferred Qualifications
- PyTorch, TorchVision 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.
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.
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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