Job Title

Job SummaryWe are looking for a skilled AI/ML Engineer to design, build, and deploy scalable machine learning solutions with a strong focus on Large Language Models (LLMs). The role involves working on data ingestion, vector databases, model integration, and optimization of AI-driven applications such as RAG systems, semantic search, and intelligent automation.Roles & ResponsibilitiesDesign, develop, and deploy AI/ML solutions using classical ML and LLM-based architectures.Build and maintain end-to-end data pipelines including data scraping, preprocessing, chunking, embedding generation, and storage.Implement and optimize vector databases (e.g., VectorDB, Pinecone, FAISS, Weaviate) for semantic search and retrieval.Develop RAG (Retrieval-Augmented Generation) pipelines integrating LLMs with structured and unstructured data sources.Monitor model performance, latency, and retrieval accuracy; fine-tune models and embeddings as required.Collaborate with product, data, and engineering teams to translate business requirements into AI solutions.Ensure best practices in model versioning, experimentation, and MLOps.Required Skills & QualificationsStrong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).Should have 3+ years of experience in similar role.Hands-on experience with LLMs (OpenAI, Hugging Face, LLaMA, Mistral, etc.).Experience working with vector databases and embedding models.Solid understanding of NLP, transformers, embeddings, and similarity search algorithms.Experience building production-grade ML systems and APIs (FastAPI, Flask).Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).