AI/ML Engineer

Key Responsibilities: Design, develop, and deploy scalable AI/ML and Generative AI solutions. Build and fine-tune Large Language Models (LLMs) using frameworks such as TensorFlow, PyTorch, and Hugging Face. Develop GenAI applications leveraging models like GPT, LLaMA, Claude, or similar. Implement RAG (Retrieval-Augmented Generation) pipelines. Design and optimize prompt engineering strategies. Develop APIs and microservices for AI solutions. Work with vector databases (Pinecone, FAISS, Weaviate, etc.). Deploy models using cloud platforms such as AWS, Azure, or GCP. Ensure model performance, scalability, monitoring, and governance. Collaborate with cross-functional teams including Data Engineering and Product teams. Maintain MLOps pipelines and CI/CD for ML deployments. Required Qualifications: 7–8 years of experience in AI/ML engineering. Strong experience in Python and ML libraries. Hands-on experience with Generative AI and LLMs. Experience with NLP, deep learning, and transformer architectures. Knowledge of LangChain, LlamaIndex, or similar frameworks. Experience with Docker, Kubernetes, and cloud deployment. Strong understanding of model evaluation, tuning, and optimization.