Data scientist

Key Responsibilities:
Develop and implement NLP-focused ML/DL solutions to power innovative, AI-driven products and features.
Build and optimize models for text classification, entity recognition, summarization, semantic search, and document understanding.
Work with traditional ML algorithms (Logistic Regression, SVM, Random Forest, XGBoost, etc.) and deep learning models (RNN, LSTM, GRU, Transformers).
Design and leverage embeddings for semantic similarity, clustering, and vector-based retrieval.
Explore and integrate Generative AI techniques into NLP applications like summarization, Q&A, and conversational systems.
Implement and optimize transformer architectures (BERT, Ro BERTa, GPT, etc.) for real-world production workloads.
Collaborate with cross-functional teams to collect, clean, and preprocess unstructured textual data.
Deploy, monitor, and maintain models using MLOps best practices including containerized deployments (Docker, Kubernetes) and CI/CD pipel...