libraries such as TensorFlow or PyTorch. Experience working with LLMs (Gemini), prompt engineering, and reinforcement learning from human feedback (RLHF). Experience with LangChain for building LLM applications with RAG pipelines and agent workflows. Practical understanding of vector search, embeddings, and retrieval-augmentedgeneration (RAG). Experience building and deploying machine learning models into More ❯
ll do: Contribute to the development of DDX — design, build, and scale intelligent systems Work on AI-driven features: LLMs, retrieval-augmentedgeneration (RAG), and AI agents Build APIs, data pipelines, and backend components (mainly Python, FastAPI/Flask) Deploy microservice-friendly solutions, often in containerised setups (e.g. Docker) Work with ElasticSearch, Weaviate, Pinecone More ❯
growth startups (Monzo, N26, Personio). Demonstrable ability in building and leading high-calibre engineering teams . Experience leading engineering teams working on Generative AI (Prompt Engineering, Fine Tuning, RAG) Competencies: Understanding Technical Requirements with a Focus on Quality: Translate product requirements into squad plans and capacity, while also having a keen eye for ensuring high coding standards, maintainability, and More ❯
