Senior Machine Learning Engineer (Knowledge Graph expert)
City of London
Permanent
Negotiable
Financial Technology
PR/561251_1761824489
Senior Machine Learning Engineer (Knowledge Graph expert)
Our client, a leading multi-strategy hedge fund managing over $20 billion of AUM, is seeking a Senior ML Engineer to join their high-performing Applied AI team, driving a new era of intelligent systems that underpin the organisations most critical decision-making. You will be developing production-grade AI systems that empower portfolio managers, analysts, and researchers with intelligent, data-driven capabilities to design scalable systems that integrate cutting-edge AI models, including LLMs and leveraging expertise in Knowledge Graphs and Graph Databases (Neo4j preferred).
Responsibilities:
- Design and build intelligent data retrieval systems that power AI-driven investment tools.
- Collaborate with ML researchers to prototype, develop, and deploy new AI/ML products.
- Work with frontend engineers to integrate backend systems into user-facing applications.
- Lead architectural decisions and contribute to the evolution of AI infrastructure.
- Participate in the full software development lifecycle, from design through deployment and support.
- Mentor junior engineers and contribute to a culture of technical excellence.
- Support critical infrastructure through on-call rotations and incident response.
Requirements:
- 10+ years of professional software engineering experience, with 4+ years focused on ML systems
- Must have expertise in Knowledge Graphs and Graph Databases (Neo4j preferred)
- Advanced proficiency in Python, including ML libraries (e.g., PyTorch, scikit-learn)
- Strong experience with distributed systems, data engineering, and API development
- Proficiency in both SQL and NoSQL databases
- Familiarity with Docker, Kubernetes, and CI/CD pipelines
- Experience integrating LLMs and RAG systems into production environments
- Familiarity with OpenAI, Anthropic Claude, or similar AI platforms
- Experience with vector databases and semantic search
- Understanding of AI agent architectures and multi-agent systems
- Exposure to observability tools like Grafana, Prometheus, or Sentry
