strong knowledge of large language models (LLMs), foundation models, and deep learning, combined with hands-on experience in fine-tuning (e.g. SFT, RLHF/RLAIF) or parameter-efficient adaptation methods such as LoRA or adapters - o strong programming skills in Python and experience with machine learning frameworks, ideally complemented by knowledge of reinforcement learning (e.g. RL, RLHF, policy optimization) * A key part of your role involves researching and applying reinforcement learning–based training approaches for intelligent . o familiarity with multi-agent systems or agentic frameworks (e.g. LangGraph, AutoGen, CrewAI), including aspects of agent safety, controllability, and human-in-the-loop approaches
mehr