Overview

Key Responsibilities: - Design scalable AI/ML architectures covering Machine Learning, Deep Learning, Generative AI, LLMs, RAG, Agentic AI, NLP, and Computer Vision.- Lead development of LLM-powered applications, advanced RAG pipelines, AI agents, and multi-agent automation workflows.- Build and optimize ML models using Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Fa

Responsibilities

• - Design scalable AI/ML architectures covering Machine Learning, Deep Learning, Generative AI, LLMs, RAG, Agentic AI, NLP, and Computer Vision.
• Lead development of LLM-powered applications, advanced RAG pipelines, AI agents, and multi-agent automation workflows.
• Build and optimize ML models using Python, PyTorch, TensorFlow, Scikit-learn, and Hugging Face.
• Work with LLMs such as OpenAI, Claude, Gemini, Llama, Qwen, and Mistral, along with vector databases such as PostgreSQL/pgvector, Pinecone, and Milvus.
• Develop AI solutions using LangGraph, LangChain, AutoGen, CrewAI, or similar frameworks.
• Deploy and monitor AI/ML applications using AWS, Azure, or GCP, Docker, Kubernetes, CI/CD, and MLOps practices.
• Lead technical teams, conduct design and code reviews, mentor engineers, and ensure quality delivery.
• Participate in client consultations, technical pre-sales, solution design, POCs, estimations, and technical presentations.
• Research emerging AI technologies and optimize model performance, scalability, security, and infrastructure costs.Required Skills : - Strong Python programming and AI/ML model development expertise.
• Hands-on experience with Generative AI, LLMs, RAG, prompt engineering, embeddings, vector databases, and AI agents.
• Knowledge of NLP and/or Computer Vision, model evaluation, fine-tuning, and deployment.
• Experience with FastAPI, Flask, or Django; REST APIs; PostgreSQL or MongoDB.
• Hands-on experience with cloud platforms, Docker, CI/CD, and MLOps; Kubernetes and GPU-based deployments are advantageous.
• Strong technical leadership, problem-solving, communication, and client-handling skills.Education &

Qualifications

• Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, Engineering, or a related field.- Proven experience delivering AI solutions from POC to production and leading engineering teams.- Experience with enterprise GenAI, multi-agent systems, open-source LLMs, multimodal AI, and international clients is preferred. (ref:hirist.tech)