LLM Engineer

Design, fine-tune, and evaluate LLMs (e.g., GPT, Llama, Claude, Mistral) for specific enterprise or domain needs.Develop custom model architectures, embeddings, and prompt engineering strategies.Implement techniques for model compression, retrieval-augmented generation (RAG), and multi-agent orchestration.Build scalable pipelines for training, evaluation, and deployment of LLM-based applications.Integrate LLMs with APIs, databases, and enterprise software systems.Work closely with Data Engineers, ML Engineers, and Product teams to translate business problems into AI solutions.Experiment with new methods for grounding, alignment, and interpretability.Minimum QualificationsBachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or related field.Strong proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, Llama Index, and LangChain.Deep understanding of LLM architectures, tokenization, embeddings, attention mechanisms, and finetuning strategies.Experience with vector databases (e.g., Pinecone, Milvus, FAISS) and RAG pipelines.Solid experience with cloud-based AI services (AWS SageMaker, Azure OpenAI, GCP Vertex AI, etc.).Strong background in NLP, information retrieval, and knowledge graph integration is a plus.