Job Details

Weekly Hours: 40

Role Number: 200630530-0157

Summary

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.

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 (https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf) .