About the role

What will you do at Apple?

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.

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.

Which skills does this role require?

PythonFacial RecognitionAdversarial Object DetectionIdentity Theft ProtectionEdge ML DeploymentBiometric SecurityMentorshipTechnical CommunicationApple WalletIdentity ProtectionEdge MLReal-time SystemsApplied ResearchProduction DeploymentM.S.

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