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Home›Jobs›Apple›Senior Computer Vision Machine Learning Engineer, Apple Wallet
Apple

About Apple

The personal technology company redefining user experience

🏢 Tech, Hardware👥 1001+ employees📅 Founded 1976📍 Cupertino, CA⭐ 4.2
B2CB2BHardwareSaaSTelecommunicationseCommerce

Key Highlights

  • Market cap of $3 trillion as of 2022
  • Over 1 billion active devices worldwide
  • Comprehensive medical plans including mental healthcare
  • Paid parental leave and gradual return-to-work program

Apple Inc. (NASDAQ: AAPL), headquartered in Cupertino, CA, is the world's most valuable company with a market capitalization of $3 trillion as of 2022. Known for its iconic products such as the iPhone, iPad, and Mac, Apple serves over 1 billion active devices globally. The company has a strong commi...

🎁 Benefits

Apple offers comprehensive medical plans covering physical and mental healthcare, paid parental leave, and a gradual return-to-work program. Employees...

🌟 Culture

Apple's culture emphasizes an obsessive focus on user experience and consumer privacy, setting it apart from competitors. The company promotes inclusi...

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Apple

Senior Computer Vision Machine Learning Engineer, Apple Wallet

Apple • Austin, Texas, United States

Posted 2 months ago🏛️ On-SiteSeniorMachine learning engineerComputer vision engineer📍 New york
Apply Now →

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.

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 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

Eeo Content

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.

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