1. PURPOSE AND SCOPE

Support the design, development, and deployment of AI-powered, data-driven applications. Work closely with R&D Engineers to gain practical experience in machine learning model development, AI research, and end-to-end AI application development while contributing to real-world AI solutions.

2. RESPONSIBILITY

• Support the development of AI-powered applications, including RAG pipelines and agentic AI workflows.
• Assist in training, fine-tuning, and evaluating AI/ML models to improve model performance, accuracy, and reliability.
• Research, prototype, and experiment with machine learning algorithms for real-world applications.
• Design and conduct machine learning and LLM experiments, benchmark results, and document findings.
• Build data pipelines and prepare datasets for AI model training and evaluation.
• Collaborate with team members to improve AI applications, resolve technical issues, and support continuous process improvement.

3. QUALIFICATION

• Final-year students or recent graduates majoring in Artificial Intelligence, Computer Science, Data Science, or related fields.
• Strong understanding of Machine Learning concepts and algorithms through coursework or personal projects.
• Hands-on experience with Python and AI frameworks such as PyTorch or TensorFlow.
• Familiarity with Generative AI tools and frameworks such as Hugging Face, LangChain, or LlamaIndex is a plus.
• Basic knowledge of RESTful APIs (FastAPI, Flask, or Django) and Git.
• Ability to read and understand English technical documentation and research papers.