AI engineer Intern
Summary
Intern designs, trains, and deploys deep-learning NLP models (LLMs, RAG, agentic AI) and helps build MLOps pipelines for scalable AI solutions.
- Design, develop, and deploy advanced Deep Learning models for NLP use cases such as Semantic Search, Information Retrieval, and Text Understanding.
- Contribute to the development and fine‑tuning of foundation models using proprietary datasets.
- Support the implementation of Generative AI solutions, including:Agentic AI Systems
- Retrieval-Augmented Generation (RAG)
- Large Language Model (LLM) Applications
- Assist in building and optimizing MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
- Work on a variety of Data Science and Data Engineering challenges involving data processing, model optimization, and performance evaluation.
- Collaborate with cross‑functional teams to transform innovative AI ideas into scalable production solutions.
Who We're Looking For
- Currently pursuing a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, Software Engineering, or a related technical field.
- Maximum of two semesters remaining before graduation.
- Strong passion for AI, Machine Learning, and continuous learning.
- Basic understanding of Python and Machine Learning concepts.
- Familiarity with Deep Learning frameworks such as PyTorch, TensorFlow, or Keras is a plus.
- Exposure to NLP, LLMs, RAG, MLOps, cloud platforms, or Data Engineering tools is advantageous.
- Self‑motivated, curious, and eager to solve complex technical challenges.