Entry Level Human Computer Interaction Jobs in California

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We are a team of computer vision and machine learning engineers building real-time perception systems, motion synthesis, and human understanding technologies for current and future Apple products. The VCV org is a centralized applied research and engineering organization responsible for developing real-time on-device Computer Vision and Machine Perception technologies across Apple products. We are looking for engineers with expertise in deep learning-focused computer vision for human understanding, motion synthesis, visual recognition, biometric algorithms, and 3D perception systems.
In this role, you will help design, build, and ship core perception technologies, motion synthesis systems, and human understanding algorithms used by millions of users across Apple's ecosystem.
Description
You will work on cutting-edge computer vision and machine learning problems, developing algorithms and systems that enable natural human-computer interaction. This includes human perception, motion synthesis, biometric recognition, 3D vision, and performance-critical real-time systems.
You will be responsible for developing and optimizing computer vision and machine learning algorithms for human understanding, including pose estimation, gesture recognition, facial analysis, and behavioral modeling. You will build motion synthesis systems and algorithms for realistic human motion generation and animation, design and implement biometric algorithms for secure authentication and identification systems, and create real-time 3D perception and tracking systems for spatial computing and AR/VR applications. As a member of a fast-paced team, you have the unique and rewarding opportunity to shape upcoming products that will delight and inspire millions of people every day.
Minimum Qualifications
Master's or equivalent practical experience, in Computer Science, Computer Vision, Machine Learning, or related technical field
Experience in deep learning with demonstrated work in at least one area of multimodal systems (e.g. vision, language, video, etc.)
Proficiency in Python and in a modern deep learning framework such as PyTorch or JAX
Experience with rapid prototyping, reproduction, and validation of research ideas
Strong mathematical foundations in machine learning, computer vision, or related fields
Experience with foundation model architectures and training methodologies
Experience working effectively in a multi-functional, collaborative environment
Preferred Qualifications
PhD, or equivalent practical experience, in Computer Science, Machine Learning, Computer Vision, or a related technical field
Demonstrated expertise in deep learning, with either: A publication record in relevant conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, COLM, etc), or a strong track record of applying deep learning techniques to real-world products
Experience with foundation models (language or multimodal) including training, fine-tuning, and deployment
Experience applying foundation models to build autonomous or semi-autonomous agents, including planning, task decomposition, and multi-step reasoning
Experience with multimodal pretraining, vision-language models, video-language models, and multimodal alignment
Experience with large-scale distributed training and model parallelism
Strong communication skills and ability to present research findings to both technical and non-technical audiences