Senior Machine Learning Engineer, Apple Wallet

Socket.dev; Cupertino (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Socket.dev in Cupertino, CA is seeking a senior computer vision and machine learning engineer to develop and deploy facial recognition and adversarial object detection systems. You will join a dynamic AI/ML team at Apple-scale collaboration, bridging research and production, with autonomy to shape methodology and implementation.

The role emphasizes cutting-edge CV/ML work, mentorship, and effective communication across teams, with production-ready deployment in a privacy- and security-focused

Qualifications

• Strong foundation in computer vision techniques and machine learning.
• Clear technical communication skills across a range of audiences.
• Strong programming abilities in Python plus at least one additional language.

Responsibilities

• Develop computer vision and ML models for facial recognition and adversarial object detection.
• Bridge research and production deployment with autonomy to influence methodology and implementation.
• Contribute to cutting-edge CV/ML initiatives that protect users and secure identities.

Skills

Computer vision

Machine learning

Technical communication

Python

Other language

Education

MS or PhD in CS/ML

Tools

PyTorch

TorchVision

Job description

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.