Lead Machine Learning Engineer

Salary: £65,000 - 105,000 per year

Requirements:

• We are looking for a machine learning or AI engineer with 5+ years of work experience.
• We require strong production-level Python development experience.
• We need deep understanding of Agentic AI systems and multi-agent architectures.
• We need proficiency in machine learning and deep learning algorithms, including NLP, neural networks, multi-class classification, decision trees, and support vector machines.
• We expect strong software and ML development fundamentals, including code quality, automated testing, source version control, and optimization.
• We require experience building GenAI frameworks and leveraging or fine-tuning LLMs.
• We need experience building or enhancing search and information retrieval systems.
• We value exposure to containerization technologies such as Docker, Kubernetes, and AWS EKS.
• We require knowledge of AWS and Azure cloud infrastructure and services such as AWS Bedrock, AWS S3, AWS Sagemaker, Azure AI Search, Azure OpenAI, and Azure Blob Storage.
• We require a masters degree or above in machine learning, data science, computer science, applied mathematics, or another research-based field.
• We would be particularly interested in candidates with familiarity with credit ratings agencies, regulations, and data products around the world.
• We value outstanding written and verbal communication skills.
• We value strong interpersonal skills and the ability to work proactively as a team player.

Responsibilities:

• We work closely with product squads to build, integrate, and deploy GenAI, multi-AI-agent, and data science solutions.
• We share best practices and learnings with other squad members.
• We design and lead the development of GenAI, AI agent, and MLOps platforms, applications, and solutions to address business challenges and improve product performance.
• We build standards and recommendations for the AI engineering tech stack and data science models used across enterprise AI use cases.
• We work with AI implementation, governance, and enterprise architecture squads to apply the appropriate standards.
• We keep abreast of the latest vendors in emerging technologies and participate in vendor evaluations and tool assessments.
• We onboard suitable solutions into the platform where appropriate.
• We communicate advanced data science and machine learning concepts clearly to business stakeholders, focusing on Fitch business applicability.
• We develop and deploy machine learning and GenAI solutions to meet enterprise goals and support experimentation and innovation.
• We collaborate with data scientists to identify innovative machine learning and GenAI solutions that leverage data to meet business goals.
• We design and develop scalable GenAI and ML workflows that leverage machine learning, GenAI, and deep learning models to meet enterprise requirements.
• We help maintain SLAs for production applications and support.
• We create metrics to continuously evaluate machine learning solution performance and improve existing solutions.
• We build with AWS and Azure cloud services to provide infrastructure, resources, and interfaces for data loading and LLM workflows.
• We use Python, Java, and large-scale workflow orchestration platforms such as Airflow to build ETL software artifacts, interface with diverse data formats and storage technologies, and incorporate them into robust data workflows and dynamic systems.

Technologies:

• Agentic AI
• AI
• Airflow
• AWS
• Azure
• Cloud
• Docker
• ETL
• Fine-tuning
• Support
• Java
• Kubernetes
• LLM
• Machine Learning
• MLOps
• Python
• AI Agents
• Network

More:

We are Fitch Group, and our Emerging Technology AI Center of Excellence is seeking a Principal Machine Learning or AI Engineer to help build and support Generative AI, machine learning, deep learning, and data science solutions across the organization. This high-impact role is based in our London or Manchester office and offers significant visibility working on flagship Fitch products. We offer the opportunity to work in the cutting-edge field of machine learning and data science, within a collaborative culture that values diverse perspectives, open exchange of ideas, and strong work-life balance. We are committed to equal opportunity and affirmative action, and we ask successful candidates to disclose securities holdings and potential conflicts of interest prior to employment.

last updated 35 week of 2026