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

Significant experience building, training and deploying machine learning models
Strong Python skills with experience using NumPy, Pandas, SciPy and modern ML frameworks such as PyTorch or TensorFlow
Experience working with large-scale unstructured data
Experience building and deploying production-ready NLP systems
Familiarity with API integrations and data acquisition pipelines
Experience implementing software engineering best practices including Git and agile development
Experience working with cloud environments (preferably AWS)
Experience with containerisation technologies such as Docker or Kubernetes (Nice to have)
Experience with frameworks such as vLLM or NeMo (Nice to have)
Knowledge of financial services NLP applications (Nice to have)
Experience designing evaluation methodologies for LLM outputs (Nice to have)
Experience building intelligent agents or multi-agent systems (Nice to have)

Remote-first working across the UK
Work abroad policy
Co-working spaces available
34 days holiday (including flexible bank holidays) and your birthday off
Company-wide off-sites
Optional Personal Development Plan
Flexible benefits platform
Protection essentials including Life Insurance, Income Protection, Critical Illness cover, and Pension (up to 5% matched employer contribution with optional increased contributions)
Private health and dental care
Potential share options
Enhanced family leave

Senior AI Engineer

Key skills