AI Research Scientist

• Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
• Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
• Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
• Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
• Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.
• Build and scale training workflows across distributed GPU infrastructure.
• Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks.
• Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development.
• Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements.
• Publish research findings in top-tier AI conferences and journals where applicable.

AI Research Engineer – Multi-Modal, Vision

• Carrying out research on deep learning audio
• Evaluating and testing AI and ML models
• Implementing and training models
• Model research, implementation, training, evaluation and inference
• Writing reports and research papers

Machine Learning Researcher – Audio

• Lead the development of AI use-case solution designs, balancing innovation with practicality.
• Oversee the entire data science / AI delivery lifecycle, from data exploration to model development/tuning to deployment, monitoring, and performance optimisation using ML and AI Ops best practices.
• Lead and work within cross-functional teams comprising of business leaders, product managers, data scientists, data engineers and ML/AI engineers.
• Partner with the Responsible AI team to embed robust ethical principles, bias mitigation techniques, and regulatory compliance into all AI development workflows.
• Coach and mentor junior data scientists and AI engineers, helping to grow team capabilities and fostering a culture of continuous learning and curiosity.
• Maintain an active view of emerging tools and techniques. Develop proof-of-concepts to demonstrate new capabilities. Guide the team in solving complex AI use cases and improving existing approaches.

AI Research Scientist jobs in United Kingdom

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AI Research Engineer – Multi-Modal, Vision

Machine Learning Researcher – Audio

Lead AI Scientist