ph3Project focus /h3 pOwn the end-to-end cloud fine-tuning of open-source LLMs on Azure - covering both Supervised Fine-Tuning (SFT) and Reinforcement Fine-Tuning (RFT), from data preparation through training, evaluation, and deployment. The role involves working with sensitive data under strict internal access controls. /p h3Key skills and Experience required /h3 ul li5+ years of engineering experience, including 2+ years hands-on LLM fine-tuning /li liStrong Python and PyTorch /li liProduction experience with Azure Machine Learning and Azure AI Foundry (managed compute, serverless fine-tuning, online endpoints, GPU quotas) /li liHugging Face stack (transformers, peft, trl, datasets,



accelerate); LoRA/QLoRA and bitsandbytes 4-bit quantization /li liSFT delivery plus working knowledge of RL/preference methods (RFT, GRPO/PPO, DPO) and reward/grader design /li liTraining-data engineering: JSONL/chat formats, curation, deduplication, split hygiene, leakage prevention /li liEvaluation rigor: task metrics, LLM-as-judge, and reading training/validation curves /li liLinux, Git, containers, and cloud GPU workflows /li liPreferred: DeepSpeed/multi-node training, quantization serving (GGUF/llama.cpp, vLLM, Ollama), Azure OpenAI fine-tuning API, RAG/GraphRAG, infrastructure-as-code (Bicep/Terraform), and Responsible-AI practices /li /ul /p #J-18808-Ljbffr

📌 AI Engineer - LLM Fine-Tuning on Azure (España)
🏢 Darwin Recruitment
📍 España