LLM Engineer

Location: London

Our client is a small, highly technical team building real-world LLM-powered systems and agentic applications - tools that are already in the hands of users, not just demos or experiments.

They focus on solving meaningful problems with production-grade AI, combining strong engineering fundamentals with thoughtful experimentation. The team is pragmatic, product-oriented, and deeply cares about clean code, fast iteration, and systems that scale.

They’re now looking for an LLM Engineer to take ownership of language-model systems end to end - from training and fine-tuning through to evaluation and deployment.

🔥 What You’ll Get

• Competitive salary - up to €110,000 salary, depending on experience
• Ownership of production LLM systems at scale, with the freedom to work across the full ML lifecycle on top of strong, production-ready infrastructure
• Close collaboration with senior researchers and experienced engineers

🧠 Your Impact

• Own the full ML lifecycle — training, fine-tuning, evaluation, and deployment of LLM systems into production
• Design, build, and scale LLM-powered and agentic applications in Python, including RAG pipelines, orchestration logic, and multi-model workflows using modern LLM APIs (OpenAI, Anthropic, Gemini)
• Deploy and operate models on production-grade infrastructure, including Kubernetes, cloud platforms, and multi-GPU environments

✅ What We’re Looking For

• Strong Python engineering fundamentals with hands-on experience building and deploying LLM-based systems in production
• Solid understanding of RAG architectures, embeddings, evaluation techniques, and modern LLM tooling (e.g. PyTorch, Hugging Face, FastAPI)
• Experience working with production ML infrastructure, including model deployment, monitoring, and iteration

🚀 What Will Make You Stand Out

• Experience with agentic workflows, tool calling, or multi-step LLM systems
• Familiarity with ML observability and experimentation tools (MLflow, W&B)
• Experience working with computer vision or multi-modal AI systems
• Comfort deploying models on cloud infrastructure (AWS/GCP, Kubernetes)

Ready to build LLM systems that power real products used at scale - not hype-driven experiments?

Apply now to work on pragmatic, production-first AI with real users and real impact.