Computer Vision Engineer

Backed by an international research team and abundant computing resources, the center focuses on core research directions including multimodal understanding and generation, vision-language large models, and embodied intelligence. This is a permanent, full-time position located in the tech hub of King's Cross, London. Key Responsibilities: Frontier Technical Breakthroughs －Develop ViT and multimodal large model architectures with improved reasoning and efficiency －Advance multimodal alignment, representation learning, and long-context modeling －Explore scalable training methods for large multimodal models －Optimize model architectures for generalization and performance Data Ecosystem Construction －Process large-scale multimodal data across images, videos, audio, and text －Build pipelines for data cleaning, filtering, annotation, and quality control －Construct and maintain datasets with versioning and reproducibility －Optimize data mixtures and sampling strategies for model training －Improve data quality through feedback-driven curation loops MLLM Systems \& Infrastructure －Build distributed training systems for large-scale multimodal models －Optimize GPU utilization, cluster efficiency, and resource scheduling －Develop open-source training frameworks for scalable model development －Engineer training, inference, and serving infrastructure －Improve scalability, stability, and performance of model systems Business Value Delivery －Integrate multimodal capabilities into assistant and content generation scenarios －Translate research into production and user-facing applications －Collaborate with product and engineering teams to deploy and iterate models Person Specification: Essential Requirements: －Academic Background: Bachelor’s degree or above in Computer Science, Mathematics, Statistics, or related technical disciplines. －Technical Skills: Proficient in Python programming with strong hands-on experience in PyTorch and deep learning frameworks. －Core Competencies: Strong algorithm development and implementation skills, solid mathematical and logical reasoning ability, and excellent cross-functional communication and collaboration skills. －Traits: Self-driven and highly motivated toward advancing artificial intelligence (AI), with strong resilience and the ability to tackle challenging technical problems. Desired: －Strong track record of publications in top-tier AI or computer vision conferences (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR) －Hands-on experience in large-scale model pre-training or fine-tuning －High-impact open-source projects or internship experience in leading technology companies within CV, NLP, or multimodal domains