Associate – AI/ML

Responsibilities

• Design and deploy AI agents and multi-agent systems using frameworks like LangChain, LlamaIndex, CrewAI, or AutoGen.
• Fine-tune LLMs (OpenAI, Llama, Mistral, Gemini) using LoRA/PEFT for domain-specific applications.
• Build RAG pipelines integrating proprietary data for context-aware responses.
• Develop predictive models for classification, regression, clustering, and forecasting.
• Manage end-to-end ML lifecycle — from feature engineering and validation to deployment and monitoring.
• Implement MLOps workflows using MLflow, Kubeflow, and deploy via Docker & Kubernetes on AWS/GCP/Azure.
• Collaborate with cross-functional teams to deliver production-grade AI solutions.
• Stay current with emerging research in LLMs, Agentic AI, and new frameworks.
• Hands-on with Python, Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow, Hugging Face Transformers.
• Experience with RAG, vector databases (FAISS, Pinecone, ChromaDB), and agent frameworks.
• Strong understanding of transformers, attention mechanisms, and fine-tuning techniques.
• Familiar with CI/CD, MLOps, containerization (Docker/K8s), and cloud platforms (AWS/GCP/Azure).
• Excellent analytical and problem-solving skills; passionate about AI innovation and continuous learning.