Multimodal LLMs Research Engineer

Summary

We are actively seeking exceptional individuals who thrive in collaborative environments and are driven to push the boundaries of what is currently achievable with multimodal inputs and large language models. Our centralized applied research and engineering group is dedicated to developing cutting-edge Computer Vision and Machine Perception technologies across Apple products. We balance advanced research with product delivery, ensuring Apple quality and pioneering experiences. A successful candidate will possess deep expertise and hands-on experience across the full lifecycle of Multimodal LLM development, encompassing early ideation, data definition, model training, and fine-tuning.

Minimum Qualifications

BS and 3+ years of relevant industry experience Demonstrated track record through publications, patents, and/or shipping relevant features Strong Python programming experience Strong PyTorch and/or JAX programming experience Ability to effectively utilize AI code development tools to accelerate the development process

Preferred Qualifications

Ph.D. with relevant research background or M.S. with relevant industry experience Strong publication record in relevant venues, such as CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc. Technical leadership experience - guiding technical efforts across diverse teams/individuals. Experience in shipping MM-LLMs in products.

Description

We are seeking a candidate with a proven track record—demonstrated through academic research, industry contributions, or a combination of both—in developing multimodal LLMs and advanced topics such as agentic AI, reasoning, and large-scale model evaluation. This role offers the opportunity to drive groundbreaking research projects, spanning foundational concepts to practical applications.

Responsibilities

Model Design & Development: Developing, implementing, and enhancing multimodal foundation models. This encompasses training or fine-tuning MM-LLMs from scratch or leveraging existing technologies to optimize performance and capabilities. Model Evaluation: Collaborating closely with cross-functional partners to define data and infrastructure requirements crucial for robust evaluation of model designs and developments. Innovation & Dissemination: Staying at the forefront of advancements in AI, machine learning, and computer vision, and applying this knowledge to foster continuous innovation within the company. Depending on your research expertise and project scope, you will have the opportunity to publish papers and/or patents to positively impact the broader community.