LLM Engineer

You will work at the intersection of machine learning, software engineering, and product to build scalable and reliable LLM-based systems.

Responsibilities: Develop, fine-tune, and evaluate large language models and embedding systems. Build and optimise inference pipelines for LLM-powered applications. Implement prompt engineering, retrieval-augmented generation (RAG), and model evaluation workflows. Collaborate with product, data, and engineering teams to integrate LLMs into production systems. Monitor model performance, latency, and cost in live environments. Stay up to date with advances in LLM architectures, tooling, and best practices.

Requirements: Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow). Hands-on experience working with LLMs and foundation models. Understanding of NLP, embeddings, transformers, and evaluation techniques. Experience deploying models to production environments. Strong problem-solving and communication skills.