Ritwik Software Technologies

3 4 years of experience in AI/ML engineering or applied data science. Strong experience in Python and ML libraries (NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch). Good understanding of LLMs, embeddings, vector databases, and NLP pipelines. Proficient in building APIs and microservices for ML model consumption (FastAPI, Flask). Experience with cloud platforms (AWS / Azure) for model training and deployment. Familiarity with Docker containers, container orchestration (Kubernetes), and CI/CD pipelines. Solid understanding of algorithms, data structures, and model evaluation techniques. Strong problem-solving skills and the ability to explain complex concepts clearly. Key Responsibilities: Design, develop, and deploy machine learning models, including classification, prediction, NLP, and deep learning solutions. Build and integrate AI solutions such as chatbots, generative AI models, and retrieval-augmented generation (RAG) frameworks. Work on end-to-end ML pipelines: data preprocessing, feature engineering, model training, evaluation, and optimization. Deploy and monitor ML models in production using tools like Docker, Kubernetes, MLflow, SageMaker, or Azure ML. Evaluate new AI/ML algorithms and frameworks; recommend adoption where appropriate. Work with cross-functional teams (product, engineering, and QA) to translate business problems into AI-driven solutions. Ensure responsible AI practices performance, security, ethics, and explainability. Document designs, experiments, results, and best practices.