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# Computer Vision Engineer

- **Company:** microTECH Global Limited
- **Location:** London, UK
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Algorithm Design, Computer Vision, Data Cleansing, Dataspaces, Python (Programming Language), Open Source Technology, Management of Software Versions, Pytorch, Delivery Pipeline, Deep Learning, Information Technology
- **Published:** August 30, 2026
- **Apply:** https://www.collegerecruiter.com/job/2815599622-computer-vision-engineer

## About the Role

* 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

## Description

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


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