Ai Ml Engineer

About the Role

We are looking for an AI/ML Engineer to design, develop, and deploy Machine Learning and Generative AI solutions. You will work on ML models, LLMs, RAG-based applications, document intelligence, and production AI systems.

Key Responsibilities

• Develop and deploy Machine Learning models for classification, prediction, and risk analysis.
• Work with XGBoost, Random Forest, Scikit-learn, and PyTorch/TensorFlow.
• Develop LLM and RAG-based applications using models such as Gemini, GPT, Llama, etc.
• Build pipelines for PDF/document extraction, chunking, embeddings, vector search, and retrieval.
• Work with vector databases like FAISS, pgvector, and Pinecone.
• Develop REST APIs using FastAPI or Flask.
• Implement prompt engineering, structured JSON outputs, and hallucination/relevance evaluation.
• Work with NLP, Transformers, embeddings, and document intelligence.
• Deploy AI/ML applications on Linux/Windows and cloud platforms (AWS/GCP/Azure).
• Optimize models and AI pipelines for performance, scalability, and cost.

Required Skills

• Strong Python programming skills.
• Good understanding of Machine Learning and Statistics.
• Experience with Scikit-learn, XGBoost, and model evaluation.
• Knowledge of NLP, Transformers, LLMs, and Generative AI.
• Hands-on experience with RAG, embeddings, and vector databases.
• Experience with PostgreSQL / SQL databases.
• Experience developing REST APIs with FastAPI or Flask.
• Basic knowledge of Docker, Git, and cloud deployment.

Good to Have

• Experience with Financial / Banking / FinTech AI applications.
• Experience with PDF / document AI and OCR.
• Experience with fine-tuning or open-source LLMs.
• Experience with AWS Bedrock, GCP Vertex AI, or similar platforms.