LlaMA Developer (Generative AI / LLM Engineer)

Role: Llama Developer (Generative AI / LLM Engineer) Location: Remote About the Role We are looking for a highly skilled Llama Developer to design, develop, and deploy AI. The ideal candidate has hands-on experience fine-tuning LLMs, building intelligent agents, integrating LLM APIs, and optimizing inference for production workloads. Key Responsibilities Build AI applications using Llama (Llama 3 / Llama Stack / Llama API / local LLM inference). Fine-tune and evaluate Llama models on proprietary and domain-specific datasets. Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases. Develop conversational agents, copilots, or knowledge assistants for business workflows. Optimize model performance via quantization, prompt engineering, and latency reduction. Integrate LLM capabilities into back-end services, microservices, APIs, or cloud platforms. Ensure compliance, safety, and responsible-AI standards for generated content. Collaborate with Data Science, MLOps, and Product teams to deploy scalable AI products. Required Skills & Experience 3–8+ years of software engineering or machine-learning experience. Proven experience with Llama models. Proficiency in Python (FastAPI, LangChain, LlamaIndex, Hugging Face ecosystem). Experience with vector databases (FAISS, Pinecone, Weaviate, ChromaDB). Strong understanding of prompt engineering, model fine-tuning, LoRA / QLoRA. Hands-on experience with GPU computing, PyTorch, Docker, Kubernetes. Familiarity with MLOps practices: CI/CD for ML, model monitoring, logging. Experience deploying models on AWS / GCP / Azure / on-prem GPU clusters. Knowledge of RAG architectures, knowledge graphs, and document parsing pipelines. Understanding of model safety, hallucination mitigation, red-team testing. Experience with llama.cpp, vLLM, Ollama, or NVIDIA Triton. Contributions to open-source LLMs or AI frameworks. Please share your updated resume at subhd@tranzeal.com