Job Description
About the Role We are building an AI-powered, multi-modal RAN optimisation platform and need a technically sharp junior engineer to help design, train, and deploy language model components at the core of the system. You will work on SLM/LLM selection, fine-tuning, RAG pipeline construction, and production-grade hallucination mitigation. Key Responsibilities Evaluate, benchmark, select, deploy and optimise SLMs and LLMs (e.g., Phi-3, Mistral 7B, Llama 3.x, Qwen 2.5) for telecom-domain tasks including prompt-based optimisation, KPI anomaly explanation, and configuration audit, within on-prem/private cloud environments with GPU acceleration. Design and implement RAG pipelines integrating PM/CM/FM data, drive test logs, and vendor documentation as retrieval corpora manage chunking, embedding, and vector store selection. Apply LoRA and QLoRA fine-tuning to adapt foundation models on operator-specific network datasets manage training runs, hyper-parameter sweeps, and evalu...