AIML - Site Lead & Lead Researcher, Foundation Models

Summary

We build frontier foundation models that power intelligent experiences at Apple. Our team works across the full training lifecycle: including pre-training foundation models, and developing mid-training approaches that bridge general capability and task-specific performance. What makes our work distinct is that we're engineering models specifically for Apple silicon and optimized for experiences that are private, personal, and deeply integrated into the OS. We're solving frontier problems in reward modeling to resist reward hacking, handling sparse and delayed rewards in agentic settings, and aligning models reliably across the spectrum from open-ended creative tasks to precise, action-taking workflows. If you're drawn to hard problems where the research and the product are inseparable, this is the team

Description

We are seeking an experienced Site Lead & Lead Researcher to oversee a strategic hub within our Apple Foundation Models (AFM) organization. You will lead a team of engineers and researchers responsible for building and advancing foundation models at Apple. Your leadership will drive infrastructure development, dataset creation, and model innovation with fundamental general capabilities such as understanding and generation of text, images, speech, videos, and other modalities. You will guide the application of these models to transform Apple products while fostering a culture of research excellence and collaborative innovation. As a Site Lead, you will balance strategic oversight with hands-on research direction, ensuring your team tackles the most challenging problems in foundation models while maintaining alignment with Apple's broader AI vision. - Lead and mentor a close-knit and fast-growing team of world-class engineers and scientists tackling some of the most challenging problems in foundation models and deep learning, including natural language processing, multi-modal understanding, and combining learning with knowledge set research direction and strategy for your site. - Identifying and developing novel applications of deep learning in Apple products while maintaining technical rigor and innovation. - Own end-to-end execution of research initiatives from problem formulation through publication, product integration, and impact measurement. - Foster collaboration across teams and stakeholder groups, bridging research, product engineering, and business objectives to ensure breakthrough ideas reach millions of users. - Drive organizational excellence through hiring, career development, and creating an environment where diverse talents thrive and contribute their best work.

Minimum Qualifications

Leadership experience: Demonstrated success leading technical teams or research groups, with evidence of growing talent and delivering results Deep learning expertise: Strong publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, KDD, ACL, ICASSP, InterSpeech) or proven track record in applying deep learning techniques to products at scale Programming proficiency: Expert-level skills in Python and one or more deep learning toolkits such as JAX, PyTorch, or TensorFlow Advanced degree or equivalent: PhD in Computer Science, related technical field, or equivalent practical experience demonstrating research leadership and technical depth Communication skills: Ability to clearly articulate complex research concepts to both technical and non-technical audiences, including executives and product teams.

Preferred Qualifications

Experience with web-scale information retrieval and search systems Track record building human-like conversation agents and natural language understanding systems Expertise in multi-modal perception for existing products and future hardware platforms Background in on-device intelligence and learning with strong privacy protections Experience leading research teams through product commercialization cycles History of mentoring researchers who have advanced to senior technical or leadership roles Demonstrated ability to work collaboratively across diverse teams and organizational boundaries Experience with responsible AI practices and ethics in machine learning