ML Data Operations Lead, Wallet, Payment & Commerce

Apple • Austin, TX

1d

About The Position

As an ML Data Ops Lead, you will focus on data acquisition, data synthesis/augmentation, data science, annotation, and data QA. This role is responsible for overseeing the end-to-end process for the machine learning data needs of AI/ML partners within Wallet, Payment, & Commerce (WPC). From conceptualization to completion, you will ensure that the data delivered to AI/ML models meets Apple's rigorous privacy and quality standards and meets regulatory/governance requirements.

Requirements

• BS/Masters degree in Computer Science, Data Science, AI/ML, or related field; or equivalent experience.
• 5+ years of experience in driving the design and development of data infrastructure and machine learning pipelines as an MLOps Engineer, Data Engineer, and/or Software Engineer.
• Experience with data exploration, data science, and analytical domains, including familiarity with a wide range of unstructured and semi-structured data assets.
• Familiarity with Machine Learning (ML development lifecycle, typical data workflows, and model metrics) and understanding of how data fits into ML.
• Excellent problem-solving and program/project management skills.
• Demonstrated capacity to build solid relationships across organizations and functions (R&D, privacy and legal, tools & infrastructure).
• Ability to consistently innovate with technical tools, processes and partnerships (internal or external) that improve value across data lifecycle.
• Scripting skills to automate tasks, compute metrics and explore use of workflows combining ML and human inputs.

Nice To Haves

• Demonstrated ability to handle complex and large scale data ops projects (annotation, collection or QA).
• Expertise is identifying erroneous, fraudulent or low quality data.
• Familiarity with pioneering ML techniques, including generative technologies (transformer architecture, computer vision, diffusion models, and multi-modal architectures).
• Experience in understanding and managing Engineering tools & infrastructure and influencing cross-team roadmaps to align with team/project needs.
• Demonstrated talent for effecting change and driving results through influence, and an ability to navigate complex organizational structures to foster collaboration across functions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees