Key Responsibilities
- Build, train, fine-tune, evaluate, and deploy Machine Learning and Deep Learning models.
- Perform feature engineering, data preprocessing, and model optimization.
- Develop predictive models for forecasting, classification, regression, and NLP use cases.
- Build Generative AI solutions using LLMs, RAG, and AI Agents.
- Monitor model performance, retrain models, and implement MLOps pipelines.
- Develop APIs using Python (FastAPI/Flask) and deploy models on cloud platforms.
Required Skills
- Strong Python programming.
- Hands-on experience with model training using Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, or PyTorch.
- Experience with hyperparameter tuning, cross-validation, feature engineering, and model evaluation.
- Knowledge of LLMs (OpenAI, Llama, Claude, Gemini), LangChain/LangGraph, RAG, and Vector Databases.
- Experience with SQL, Git, Docker, and cloud platforms (AWS/Azure/GCP).
Education
- Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
