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Listed on LSEG’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads a team of data scientists and machine learning engineers building AI-powered products for financial markets, combining technical expertise with people leadership to deliver production-grade solutions. It suits experienced engineering managers comfortable with both hands-on AI development and strategic team building in a fast-moving AI organization.
Our summary, not LSEG’s wording. The full posting is on their site.
Skills this role names
- Azure Machine Learning
- CI/CD
- Deep Learning
- Generative AI
- Hugging Face
- Kubernetes
- LangChain
- MLOps
- Python
- PyTorch
- Retrieval-Augmented Generation
- scikit-learn
- Semantic Kernel
- TensorFlow
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What they ask for
Required
- Track record leading high-performing data science and ML engineering teams
- Delivered large-scale AI initiatives from concept to production with measurable impact
- Deep expertise in LLMs, Generative AI, and Deep Learning
- Hands-on experience with LLM evaluation, model validation, and prompt engineering
- Advanced Python proficiency with modern AI frameworks
- Experience building and scaling enterprise AI platforms and intelligent applications
- Strong understanding of model observability, monitoring, and operational reliability
- Cloud-native AI development experience with Azure or AWS AI services
- MLOps and LLMOps implementation at scale
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Physics, or related quantitative field
Nice to have
- Leadership experience in financial services, capital markets, or data-intensive domains
- Experience developing multi-agent systems, autonomous workflows, and AI assistants
- Knowledge of reinforcement learning, fine-tuning, and model compression
- Familiarity with Knowledge Graphs, vector databases, and semantic search
- Understanding of Responsible AI, model governance, and regulatory compliance
- DevOps and containerization experience
- Contributions to AI community through publications, patents, or open-source work
- Master's degree or PhD