Data Strategy & Acquisition Lead - AI/ML Systems

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something.

Description

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.

Responsibilities

• Design and evolve long-term data roadmaps aligned with research priorities and model scaling trajectories.
• Define metrics and feedback loops to evaluate dataset quality and model impact.
• Define data requirements in close collaboration with Algo and Research teams for a range of CV and MM-LLM use cases.
• Build acquisition strategies across modalities - including real-world collection, synthetic generation, web scraping, and partnerships.
• Lead cross-functional planning and execution, coordinating with multiple cross functional engineering teams.
• Own project execution, ensuring data delivery on time and at the required quality
• Balance cost, scalability, and quality tradeoffs, and adapt strategies based on evolving model needs.
• Track progress, unblock issues, and communicate clearly across technical and non-technical audiences.

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

• 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.