Senior ML Engineer

Senior Machine Learning Engineer

Salary: £70,000–£90,000

Location: London (Hybrid)

The Opportunity

We're looking for a Senior Machine Learning Engineer to help design, build, and deliver next-generation AI systems. You will work across LLMs, retrieval-augmented generation (RAG), and modern agent frameworks to transform large, unstructured data into meaningful insights and production-ready capabilities.

This is a hands-on role within a growing AI team, offering the chance to shape architecture, build scalable pipelines, and ship features that directly impact users.

Responsibilities

• Develop, integrate, and fine-tune LLMs for natural-language understanding, reasoning, and workflow automation.
• Build agentic/LLM-driven workflows for multi-step decision making across diverse data sources.
• Architect and deliver ML features such as pattern recognition, entity extraction, and intelligent automation.
• Design scalable data and streaming pipelines capable of handling large, heterogeneous datasets.
• Build and optimize vector search, embeddings, and RAG systems to support high-quality retrieval.
• Deliver production-ready APIs, services, and model inference systems.
• Manage deployment, monitoring, observability, and continual improvement of ML models.
• Evaluate model performance using offline metrics, A/B tests, latency and cost optimisation.
• Work closely with product and domain experts to translate requirements into robust ML solutions.

Who You Are

• Strong proficiency in Python and experience with PyTorch or TensorFlow.
• Practical experience with LangChain, LangGraph, AutoGen, or similar LLM/agent frameworks.
• Skilled in prompt engineering, integrating foundation model APIs, and LLM fine-tuning techniques.
• Expertise in building RAG systems, vector databases (e.g., Pinecone, Weaviate), and embedding pipelines.
• Experience with ML/LLMOps for monitoring, evaluation, and traceability.
• Solid understanding of distributed systems, microservices, and real-time data processing.
• Comfortable with containerisation and cloud infrastructure (Docker, AWS, Terraform, etc.).
• Experience deploying production AI systems with a strong focus on reliability and safety.
• Background in NLP, information extraction, or large-scale unstructured data processing.
• Experience in security, intelligence, or data-heavy platforms is a plus but not required.

Education & Experience

• Degree in Computer Science, AI/ML, or equivalent practical experience.
• Demonstrated experience building and shipping ML/AI products at scale.
• Proven track record working with LLMs, RAG pipelines, or agent-based systems.

Work Environment

• Hybrid: mix of remote work and in-person collaboration in our London office.
• Flexible schedule within standard business hours.