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Job Description

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- AI systems. You will work across LLMs, retrieval-augmented (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- 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.

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