Protecting millions of users from fraud and securing their identity every day by working on cutting-edge computer vision technology in the field of facial recognition and adversarial object detection.
Requirements
- Strong foundation in computer vision techniques and machine learning
- Strong programming abilities in Python plus at least one additional language
- 5+ years of relevant experience in Computer Vision Machine Learning
- 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
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
- 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
- See your work from methodology through implementation, with the autonomy to make meaningful technical decisions in a supportive, high-visibility environment.
- Combine applied research with production deployment.
Other
- Proven mentorship experience with demonstrated positive outcomes
- Clear technical communication skills across a range of audiences
- Mentor early-career engineers, supporting their growth and project success
- Partner with cross-functional stakeholders, translating complex technical concepts and instilling trust
- M.S. or PhD in computer science, machine learning, or a related field or equivalent practical experience.
