Senior ML Engineer
hace 3 días
City of London
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.