Visual Intelligence and Machine Learning Research Scientist

Apple is where individual imaginations gather together committing to the values that lead to great work. Every new product we build every service we deliver is the result of us making each others ideas stronger. Here youll do more than join something youll add team sits at the intersection of computational neuroscience visual intelligence and AI translating cutting-edge research directly into experiences that users see and feel every day. We prototype algorithms from first principles all the way through to shipping features working hand-in-hand with app teams and designers so that the science we build has immediate tangible impact on how people interact with Apple products. If you want your research to matter beyond a paper this is where that happens.

We are looking for a Visual Intelligence and Machine Learning Scientist who bridges computational neuroscience and modern AI. You will build models that reason about human visual attention behavioral states comfort and perceptual salience from video and multimodal sensor streams. You will have a track record of original research contributions a drive to deploy algorithms on real-world data and the versatility to take an idea from exploratory research to polished user experience.

Apply large and on-device vision foundation models multimodal transformers and generative AI to build visual intelligence systems that predict saliency understand scene context and estimate perceptual state from video and sensor and own end-to-end AI pipelines: from data curation and model training to fine-tuning and adapting pretrained vision-language and multimodal foundation models for on-device real-time multimodal AI systems that fuse visual signals with IMU depth and temporal context improving robustness and perceptual fidelity across diverse real-world generative AI and computational modeling to develop learned representations and priors that extend model generalization beyond labeled data across devices environments and user with app teams UX designers and systems engineers to translate algorithmic outputs directly into user-facing features on iOS macOS and spatial computing and track perceptual and behavioral KPIs at the object scene and user level to rigorously validate algorithm quality and drive continuous at the frontier of visual intelligence multimodal AI and computational neuroscience rapidly prototyping novel ideas and carrying the most promising from research to shipped product.

MS with 3 years of research experience in Computer Science Biomedical Engineering Computational Neuroscience Applied Mathematics or a related field with a focus on computer vision or machine research contributions to visual intelligence or perceptual modeling including peer-reviewed publications or equivalent industry expertise in visual perception: saliency modeling object detection and localization optical flow depth estimation and multimodal learning including sensor fusion with IMU and temporal hands-on experience training and deploying deep learning models using modern frameworks (PyTorch TensorFlow JAX) and Python scientific libraries (NumPy OpenCV scikit-learn).nStrong mathematical foundations in linear algebra probability optimization and signal processing with experience in large-scale dataset curation and evaluation communication and collaboration skills; ability to thrive in a fast-paced environment alongside scientists engineers designers and domain experts from the behavioral and cognitive sciences.

PhD in Computer Science Biomedical Engineering Computational Neuroscience Applied Mathematics or a related field with a focus on computer vision or machine with vision foundation models vision transformers (ViT) and adapter-based fine-tuning for perceptual or behavioral downstream with generative AI and neural rendering approaches (diffusion models implicit neural representations) as components of computational perception in computational modeling of perceptual or behavioral phenomena: modeling user state comfort visual salience or behavioral response from video or sensor developing or deploying models for spatial computing platforms (AR/VR headsets iOS macOS).nTrack record of shipping algorithms in resource-constrained real-time on-device inference to be versatile across a multi-faceted role moving fluidly between deep research engineering rigor and direct collaboration with product and design teams to bring science to life in user-facing features.