Job Description

Description

We are seeking professionals with a background in developing advanced agentic systems. The role involves designing, implementing, and optimising multi-agent architectures using frameworks such as Autogen and CrewAI. This includes developing bespoke tooling and custom function calls to enhance agent interoperability while applying Retrieval-Augmented Generation (RAG) methodologies for task execution and problem-solving. Additionally, the role requires expertise in fine-tuning large language models, particularly open-source models such as Llama. Understanding of techniques such as Supervised Fine Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF) is a plus. The ideal candidate will have demonstrable, hands-on experience in agentic systems development and an understanding of the underlying technical concepts, including model optimisation and custom function integration. A solid foundation in Natural Language Processing is important, complemented ...

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