Multimodal Vision AI Scientist: Research & Impact in London

Multimodal Vision AI Scientist: Research & Impact in London

London Full-Time 70000 - 90000 Β£ / year (est.) No working from home possible
IC Resources Recruitment

At a Glance

  • Tasks: Join a global team to develop cutting-edge AI and vision models.
  • Company: Leading tech company at the forefront of AI research.
  • Benefits: Competitive salary, flexible working, and opportunities for growth.
  • Other info: Collaborative environment with access to large-scale datasets.
  • Why this job: Make a real-world impact with innovative AI solutions.
  • Qualifications: Experience in computer vision and strong research skills.

The predicted salary is between 70000 - 90000 Β£ per year.

IC Resources Recruitment in London is seeking a Computer Vision Research Scientist to join a global technology company at the forefront of AI research and innovation. You will contribute to multimodal AI research, develop state-of-the-art vision transformers and multimodal models, and collaborate with an international team to translate research into real-world applications.

The role offers opportunities to work on large-scale datasets and scalable training systems, with close ties to engineering.

Multimodal Vision AI Scientist: Research & Impact in London employer: IC Resources Recruitment

At IC Resources, we pride ourselves on being an innovative employer that champions flexibility and equity in the workplace. Our collaborative culture fosters creativity and growth, providing employees with unique opportunities to shape the future of AI technology while enjoying a work-life balance that suits their needs. Join us in Oxford, where your contributions will directly impact the development of cutting-edge AI solutions in a supportive and dynamic environment.

IC Resources Recruitment

Contact Details:

IC Resources Recruitment Recruitment Team

We think you need these skills to ace Multimodal Vision AI Scientist: Research & Impact in London

Computer Vision
AI Research
Vision Transformers
Multimodal Models
Collaboration
Large-Scale Datasets
Scalable Training Systems