Machine Learning Engineer, Computer Vision - Strategic Data Solutions

• Translate business needs into technical solutions. Work with program managers, data scientists, and business partners to incorporate analytic solutions into business processes
• Explore tabular and image datasets to identify patterns of fraudulent behavior
• Move quickly to combat adversarial attacks by developing and deploying updated models
• Analyze data and communicate findings to audiences with various technical backgrounds (e.g., engineers, program managers, and executives)
• Coordinate with engineers and system administrators to deploy analytics to a real-time decisioning platform
• Identify and implement new data science tools to complement the existing capabilities of the team

M.S. or Ph.D. in Computer Science, Machine Learning, Engineering, or other technical field with experience in computer vision or machine learning or equivalent 2 years of proven experience
Practical experience and theoretical understanding of computer vision methods (e.g., local feature matching) or deep learning models (e.g., CNN)
Ability to code and debug in a general programming language such as Python or Java
Ability to extract business insights from data and identify the stories behind the patterns
Ability to navigate complex systems spanning toolchains and teams

Ability to use a querying language such as SQL to extract insights from data
Demonstrate ability to think holistically about system structures and interactions in order to anticipate technical, business, and customer impact
Effective communication skills to translate complex concepts and analysis into concise, business-focused solutions
Team-oriented skills and values to facilitate effective collaboration with business and technical partners

Apple's Strategic Data Solutions (SDS) team is looking for a hard-working individual who is passionate about implementing and operating analytical solutions that have direct, measurable impact to Apple and its customers. As a CV MLE on the SDS team, you will build end-to-end solutions for preventing fraud, waste, and abuse while safeguarding the customer experience. The day-to-day work consists of identifying new fraud leads by connecting different data sources together; working with a team of annotators to curate a labeled image dataset; building computer vision pipelines or training ConvNet models; deploying the analytic product into a real-time decisioning platform; and ensuring ongoing operational excellence by monitoring and making operational adjustments. The adversarial nature of fraud and the large scale of the business make for exciting challenges. On this team, we apply a variety of data science approaches towards the mitigation of fraud!

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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.