AI/ML

Python, SQL, Data Structures & Algorithms Machine Learning, Deep Learning, TensorFlow, PyTorch, Scikit-Learn Generative AI, LLMs, LangChain, RAG, Prompt Engineering AWS/Azure/GCP, Docker, Kubernetes, MLOps, CI/CD NLP, Vector Databases (FAISS/Pinecone/ChromaDB), Pandas, NumPy, API Development

Design, develop, train, test, and deploy Machine Learning models for business use cases. Build and optimize predictive, classification, recommendation, and forecasting models. Develop and implement NLP, LLM, and Generative AI solutions. Perform data collection, cleaning, feature engineering, and exploratory data analysis. Fine-tune and optimize pre-trained models for domain-specific applications. Develop APIs and microservices to expose AI/ML models. Implement MLOps practices for model deployment, monitoring, versioning, and retraining. Work with large datasets and distributed processing frameworks. Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions. Monitor model performance, accuracy, and drift in production environments. Create technical documentation and best practices for AI/ML implementations.