Machine learning Engineer - Intern

Research and Development: Collaborate with senior team members to conduct research on advanced NLP techniques, including RAG models and prompting methodologies.
Model Development: Design, implement, and optimize machine learning models for NLP tasks such as text classification, entity recognition, sentiment analysis, and text generation.
Data Preprocessing: Clean, preprocess, and analyze large-scale text data to extract meaningful features and insights for model training.
Evaluation and Testing: Evaluate the performance of NLP models using appropriate metrics and conduct rigorous testing to ensure their robustness and scalability.
Documentation: Document experimental findings, methodologies, and results in a clear and concise manner for internal knowledge sharing and external publications.
Collaboration: Work collaboratively with cross-functional teams including software engineers, data scientists, and product managers to integrate ML models into production systems.
Learning and Growth: Stay updated with the latest advancements in NLP and ML research by attending conferences, reading academic papers, and participating in online courses.