3 of 3 Permanent Vertex AI Jobs in Lancashire

stakeholders Demonstrable experience deploying machine learning solutions in a production environment, and familiarity with version controls systems (e.g. Git) Desirables: Experience with cloud-based ML infrastructure, particularly GCP (Vertex AI, BigQuery), or equivalent (e.g. AWS, Azure) Exposure to orchestration tools such as Kubeflow pipelines or Airflow Familiarity with DBT or similar tools for modelling data in More ❯

LEAD AI ENGINEER LIVERPOOL 2 DAYS ON-SITE INSIDE IR35 A hands-on, innovation-driven role focused on rapidly prototyping advanced AI systems using LLMs, autonomous agents, and semantic search. The engineer will work across the full stack-from prompt engineering and memory management to UI and cloud deployment-using tools like LangChain, CrewAI, and vector … A2A agents). Implement multi-step reasoning, memory modules, and RAG pipelines. Use frameworks like LangChain, LangGraph, CrewAI, and tools like Pinecone, FAISS. Optimize performance and ensure responsible AI practices. Deploy via cloud platforms (AWS Bedrock, Azure AI, Google Vertex). Build UIs (Streamlit, Gradio, React) and integrate APIs and databases. Preferred Skills Experience … with multi-agent systems and ethical AI. Familiarity with advanced model configuration and reusable AI components. Job Title: Lead AI Engineer Location: Liverpool, UK Job Type: Contract Trading as TEKsystems. Allegis Group Limited, Maxis 2, Western Road, Bracknell, RG12 1RT, United Kingdom. No Allegis Group Limited operates as an Employment Business and Employment Agency as set More ❯

banking for good. Responsibilities: As a Data Scientist in the Machine Learning Observability & Governance team, you will play a crucial role in enabling Starling Bank to maximally exploit AI in line with its risk appetite, while ensuring ethical and responsible AI practices. Your responsibilities will include: Empowering Decision-Making through Education: Educate model owners and other … are responsible. Stakeholder Communication & Visibility: Ensure clear communication and good visibility with stakeholders such as risk teams, regarding how data scientists at Starling observe and manage ML and AI models. Observability Centre of Excellence: Support colleagues in enhancing their observability work by maintaining existing observability tooling, assisting in identifying key metrics to monitor, and providing expert advice on … internally-developed model behaviour characterisation techniques. Innovate and Implement Novel Methods: Develop and implement cutting-edge techniques and frameworks to deepen our understanding of AI and ML model behaviour, enabling the safe and effective exploitation of advanced AI. This includes contributing to initiatives such as LLM-as-a-judge, RAG evaluations, and agentic workflow assessment. To thrive in More ❯