Applied Machine Learning Research Engineer - Multimodal Generative AI for Human Understanding

We're starting to see the incredible potential of generative models, and many applications in the computer vision and machine learning domain that previously appeared infeasible are now within reach. We are looking for a highly motivated and skilled Applied Machine Learning Research Engineer to join our team in the Video Computer Vision group and help us push the boundaries of human understanding. The Video Computer Vision org has pioneered human-centric real-time features such as FaceID, FaceKit, and Gaze and Hand gesture control which have changed the way millions of users interact with their devices. We balance research and product requirements to deliver Apple quality, pioneering experiences, innovating through the full stack, and partnering with HW, SW and AI teams to shape Apple's products and bring our vision to life.

Description

You will drive ground breaking research in AI and computer vision, focusing on generative models. Your contributions will span foundational research to practical applications, encompassing the design, implementation, and evaluation of novel algorithms and models. Specifically, you will concentrate on human understanding - researching and learning human motion, activities, and representations. A key aspect of your work will involve exploring and developing approaches for generating multi-modal outputs, such as human motion, voice, and images.

This role offers the unique opportunity to innovate, bring your ideas to life, and transition your research into production-ready features that will empower products used by millions worldwide. You will collaborate closely with a diverse team of experts, including researchers, data scientists, software engineers, human interface designers, and application domain specialists, fostering continuous learning and knowledge exchange. By staying abreast of the latest advancements in AI, machine learning, and computer vision, you will directly drive innovation, influence the evolution of Apple's products, and profoundly improve the lives of our users.

Preferred Qualifications

Hands-on experience with training production-quality models based on diffusion or a similar approach.

Publication record in relevant venues in AI, machine learning, computer vision, or computers graphics.

PhD in Computer Science, Electrical Engineering, or a related field with a focus on AI, machine learning, computer vision, or computer graphics.

Minimum Qualifications

Experience in developing, training/tuning generative models, with a focus on generating multi-modal outputs such as voice, images, human motion, 3d structure, or similar.

Experience with at least one deep learning framework such as PyTorch, JAX, or similar.

Strong programming skills in Python with solid software engineering fundamentals.