Lead Machine Learning Engineer (London)

Overview

As a Principal ML/AI Engineer at Fitch Group, you will lead the development and deployment of Generative AI, multi-Agent systems, and data science solutions across the enterprise. You will collaborate with product squads to scale Gen AI capabilities while upholding governance and best practices. The role offers visibility on flagship products and a path to influence the AI engineering standards across the organization. You will work in a hybrid London or Manchester office environment with cutting-edge ML and data science opportunities.

Pay / Benefits

• hybrid work model
• high visibility role
• opportunity to work on flagship products
• vibrant tech community
• focus on governance and responsible AI
• global collaboration

Responsibilities

• Collaborate with product squads to build, integrate and deploy GenAI, multi-Agent AI, and data science solutions.
• Design and lead Gen AI, AI Agents, and MLOps platforms and workflows to address business challenges and improve product performance.
• Establish standards for AI engineering tech stack and data science models across enterprise use cases; align with governance and EA squads.
• Stay informed on emerging tech vendors and participate in tool evaluations and onboarding where appropriate.
• Explain complex data science concepts to business stakeholders in practical terms and show applicability to Fitch.
• Develop and deploy ML/GenAI solutions to drive enterprise goals and enable experimentation and innovation.
• Partner with data scientists to identify innovative ML/GenAI solutions aligned with business goals.
• Create scalable GenAI/ML workflows and systems to meet enterprise requirements; maintain SLAs for production apps and define performance metrics.
• Leverage AWS and Azure cloud services; use Python/Java and Airflow to build ETL artifacts and robust data workflows.
• Maintain production performance metrics and optimize ML solutions; ensure integration with diverse data formats and storage technologies.

Key requirements

• 5+ years of ML/AI engineering experience
• Production-quality Python development experience
• Deep understanding of agentic AI systems and multi-agent architectures
• Strong ML/DL knowledge (including NLP, neural networks, multi-class classifications, decision trees, SVM)
• Solid software and ML development fundamentals (code quality, automated tests, version control, optimization)
• Experience building GenAI frameworks and finetuning LLMs
• Experience building/enhancing search and information retrieval systems
• Exposure to containerization (Docker, Kubernetes, AWS EKS)
• Knowledge of AWS and Azure infrastructure/services (e.g., AWS Bedrock, S3, SageMaker; Azure OpenAI, Azure AI search, Azure blob storage)
• Master’s degree or higher in ML/DS, CS, applied math, or related field

• Strong communication skills
• Collaborative and proactive mindset
• Ability to work in a distributed, fast-paced environment
• Python
• Java
• GenAI frameworks and LLM fine-tuning

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