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., Frontier Technical Breakthroughs

• Develop ViT and multimodal large model architectures with improved reasoning and efficiency
• Advance multimodal alignment, representation learning, and long-context modeling
• 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

• Optimize GPU utilization, cluster efficiency, and resource scheduling
• 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

• 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.
• Strong track record of publications in top-tier AI or computer vision conferences (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR)
• High-impact open-source projects or internship experience in leading technology companies within CV, NLP, or multimodal domains