Senior ML Engineer

Key details

• Build and optimise LLM-powered systems
• Architect, fine-tune and optimise machine learning models including LLMs and classical ML approaches
• Experiment with modern architectures such as Transformers and Mixture-of-Experts
• Apply efficient training and fine-tuning techniques including LoRA and parameter-efficient methods
• Develop robust evaluation approaches to measure model quality and reliability
• Develop scalable AI systems
• Build and deploy production-grade NLP pipelines and services
• Ensure models operate efficiently with low latency and high availability
• Integrate models into scalable cloud infrastructure and real-world applications
• Lead the acquisition, processing and governance of large structured and unstructured datasets
• Apply exploratory data analysis and validation techniques to improve training pipelines
• Ensure data privacy and governance standards suitable for financial services
• Contribute to DevOps and MLOps pipelines
• Implement robust version control, testing and CI/CD workflows
• Support reliable deployment and monitoring of models in production environments
• Mentor engineers and contribute to the technical growth of the team
• Work closely with product, engineering and data teams to deliver AI solutions
• Stay at the forefront of AI and NLP research, applying new approaches where they add value
• Company mission
• To transform the financial services industry through AI