Architecture Implementation: Build and optimize RAG (Retrieval-Augmented Generation) systems or AI Agents frameworks to enable models to effectively utilize external knowledge bases.
Data Processing: Establish automated Data Pipelines to process unstructured data (text, images, code) for model. Agent collaboration: Collaborate with software engineers to design Agent to Agent structure, including behavior tracing, security guardrails, agent coordination to conduct meaningful output.
Research: Study the latest technical reports or academic papers to assess the feasibility of applications.
Programming Languages: Proficiency in Python (core for data science) and C# (for application performance optimization).
ML Frameworks: Hands-on experience with PyTorch, TensorFlow, or JAX for model building and training.
Core Theory: Solid foundation in Machine Learning, Natural Language Processing (NLP) Data processing: Utilize tools such as SQL and Vector DB to store and process data. Student of the last 2 semesters of engineering bachelor / master's degree