Data Strategy & Acquisition Lead - AI/ML Systems

Apple • Sunnyvale, CA

76d

About The Position

We’re building the next generation of AI systems — combining classic computer vision with cutting-edge multimodal LLMs. None of this is possible without the right data. As the Data Strategy & Acquisition Lead, you’ll be at the heart of our AI innovation engine. You will work across teams to define, source, and deliver the high-quality, large-scale datasets that power our models. This is not just about collecting data — it’s about understanding what data is needed, why it’s needed, and how to get it at scale, efficiently and ethically. You’ll shape how our organization understands, prioritizes, and scales data — ensuring that every dataset directly advances model capability and real-world performance. You’ll partner with research scientists, hardware and software teams, operations, simulation experts, and infrastructure engineers to shape our data strategy from concept to execution.

Requirements

• BS and a minimum of 3 years relevant industry experience.
• Experience in data strategy, data operations, or technical program management for AI/ML systems.
• Experience managing budgets, vendors, or external data partnerships.

Nice To Haves

• Master’s or PhD in a technical field (CS, EE, or related).
• Experience building or managing datasets for multimodal LLMs or large-scale computer vision systems.
• Familiarity with modern data infrastructure stacks — distributed storage, labeling platforms, and workflow orchestration tools.
• Experience with privacy-preserving data techniques, annotation quality frameworks, and dataset bias mitigation.
• Knowledge of simulation platforms, synthetic data generation, and photorealistic rendering.
• Track record of building or scaling data pipelines supporting research-to-production model development.
• Understanding of trends in data scaling laws, foundation models, and self-supervised learning.

Responsibilities

• Define, source, and deliver high-quality, large-scale datasets for AI models.
• Understand the data needs and how to acquire it efficiently and ethically.
• Shape the organization’s understanding and prioritization of data.
• Ensure datasets advance model capability and real-world performance.
• Collaborate with research scientists, hardware and software teams, and other stakeholders.

What This Job Offers

• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees