Senior Computer Vision Machine Learning Engineer, Apple Wallet

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. 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 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 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.

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