Artificial Intelligence Engineer

Role Overview : We’re looking for an AI Engineer for one of our Tier-1 IT clients with hands-on experience in building, fine-tuning, and optimizing LLM-based applications. The ideal candidate will have solid expertise in RAG (Retrieval-Augmented Generation) architectures, parameter-efficient fine-tuning (e.g., LoRA), and model quantization techniques for deployment efficiency.Key Responsibilities: ●Design, implement, and optimize end-to-end LLM-based solutions for real-world applications. ●Develop and maintain RAG pipelines integrating vector databases, embeddings, and retrieval techniques. ●Fine-tune pre-trained language models using LoRA or similar methods. ●Apply quantization and optimization strategies to deploy models efficiently on constrained environments. ●Collaborate with data scientists, software engineers, and product teams to integrate AI features into production systems. ●Monitor, evaluate, and continuously improve model performance and reliability.Required Skills: ●3–5 years of experience in AI/ML development or applied NLP. ●Proficient in Python and frameworks such as PyTorch or TensorFlow. ●Strong understanding of LLM architectures (e.g., GPT, Llama, Falcon, Mistral). ●Experience with RAG frameworks (LangChain, LlamaIndex, or custom retrieval setups). ●Hands-on knowledge of LoRA, PEFT, and model quantization (GPTQ, AWQ, or similar). ●Familiarity with vector databases like FAISS, Pinecone, or ChromaDB. ●Good understanding of prompt engineering and evaluation techniques. ●Cloud deployment experience (AWS, Azure, or GCP) is an advantage.Preferred Skills : ●Exposure to open‑source models and fine-tuning pipelines. ●Experience integrating AI models into web or enterprise products. ●Knowledge of containerization and MLOps (Docker, Kubernetes, MLflow).

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