Machine Learning Research Engineer

The Human and Object Understanding team (HOUr) in the Intelligent System Experience (ISE) organization is looking for Research Engineers with a strong foundation in Machine Learning and Computer Vision to develop the next generation of multi-modal Human Sensing technologies. You will be part of a fast-paced impact-driven Applied Research organization building foundation models for facial and full-body perception and working on cutting-edge machine learning that is at the heart of the most loved features on Apple platforms including Apple Intelligence Camera Photos Visual Intelligence etc.

As a Machine Learning Research Engineer you will be responsible for designing and developing cutting-edge AI/ML models for Human Sensing with a focus on building robust cross-domain identity recognition systems. Multi-modal Human Sensing is a foundational capability that powers intelligent experiences based on key human traits such as identity expression clothing action gesture gaze and human-object interaction. Major Apple Intelligence experiences such as personalized Natural Language Search Memories Creation as well as personalized Image Generation are powered by our ability to learn robust representations of visual human traits. Efficient real-time visual human sensing powers flagship Photography experiences such as Cinematic mode and Photographic Styles communication experiences such as Center Stage and paves the way for more natural human-device interactions e.g. with the DockKit framework.

Designing implementing and deploying state-of-the-art visual recognition foundation models for facial and full-body data quality excellence through strategic dataset curation validation and generation to support world-class model tools and frameworks for systematic failure analysis identifying edge cases and driving continuous model interacting with all cross-functional stakeholders to gather product requirements and translating these into actionable plans for ML research and communicating results and insights to partners and senior leaders providing clear and actionable current with the latest trends technologies and best practices in machine learning multi-modal foundation models computer vision and natural language contributing to Apples ML community by disseminating research ideas and results enhancing shared infrastructure and mentoring fellow practitioners.

Masters or Ph.D. in Computer Science Computer Engineering or related fields or equivalent professional experience in Computer Vision (CV) and Machine Learning (ML) research and track record of training fine-tuning and evaluating deep learning models for vision tasks using modern ML in research and innovation demonstrated through publications in top-tier journals or conferences patents or impactful software in Python PyTorch or equivalent deep learning frameworks.

Expert-level knowledge of state-of-the-art methods in face recognition or other facial analysis and biometric -on experience training and scaling multi-modal large language models (LLMs) or large-scale vision-language models (VLMs)nExperience with on-device ML model optimization (knowledge distillation quantization pruning) or production-grade ML pipelines.