Senior Machine Learning Engineer – LLM Fine-Tuning & Agentic Systems

**Job Summary** We’re seeking a Senior Machine Learning Engineer to lead the design, training, and deployment of domain\-specific AI systems. You’ll own the full lifecycle, from ML model training and evaluation to LLM fine\-tuning (LoRA/PEFT) and agentic system development using frameworks such as Hugging Face, Ollama, LangChain, and n8n. Your work will bridge data engineering, AI model optimization, and tool orchestration via MCP / API to deliver intelligent, context\-aware solutions. **Key Responsibilities** • Prepare, clean, and label datasets for ML and LLM training. • Train, fine\-tune, and optimize LLMs and traditional ML models using Hugging Face Transformers, PyTorch, and scikit\-learn. • Implement LoRA/PEFT fine\-tuning pipelines for open\-weight models (Llama, Mistral, Falcon, etc.). • Build RAG pipelines using embeddings, vector stores, and retrieval APIs. • Develop and deploy agentic workflows via LangChain, n8n, or custom microservices. • Integrate models with external APIs and data systems through MCP or custom connectors. • Evaluate model quality (accuracy, F1, perplexity, hallucination rates) and optimize performance. • Manage deployments on GPU\-based servers (AWS EC2, GCP, azure) and automate versioning in Ollama. **Requirements** • 4\+ years of experience in machine learning model development, training, and deployment. • Strong proficiency in Python, PyTorch, and Transformers. • Proven hands\-on experience with LLM fine\-tuning (LoRA/PEFT) and RAG architecture design. • Familiarity with LangChain, n8n, FastAPI, Node.JS, Docker, and Linux. • Experience integrating models with APIs, databases, and external systems. • Understanding of agentic architectures, context management, and MCP tool protocols.