AI / ML Engineer

• Proficiency in Python and ML libraries: Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch
• Strong understanding of Machine Learning algorithms, statistics, and probability
• Hands-on experience with end-to-end ML workflows and model evaluation techniques
• Familiarity with MLOps tools: MLflow, Kubeflow, Docker, CI/CD pipelines
• Basic knowledge of cloud platforms such as AWS, Azure, or GCP for model deployment GenAI

(Mandatory):

• Hands-on experience with Generative AI concepts and applications
• Working knowledge of LLMs, prompt engineering, and fine-tuning techniques Experience with frameworks/tools like LangChain or similar
• Understanding of RAG (Retrieval-Augmented Generation) and AI agents
• Exposure to OpenAI APIs or other LLM-based integrations