JOB PURPOSE:
Develop and evaluate AI/ML models and prototypes to support research and product innovation. Create, train, and fine-tune AI models using localized and domain-specific data.
Design, implement, and optimize AI applications using modern frameworks and tools. Conduct experiments, analyze results, and document findings for continuous improvement.

KEY RESULT AREAS / RESPONSIBILITIES
Qualifications & Skills Technical Skills
Proficiency in Python programming.
Basic knowledge of machine learning algorithms such as regression, classification, clustering, and neural networks.
Familiarity with AI/ML libraries and frameworks such as: PyTorch
Understanding of data preprocessing, feature engineering, and model evaluation techniques. Basic knowledge of Large Language Models (LLMs) and Generative AI concepts is an advantage.
Familiarity with prompt engineering, Retrieval-Augmented Generation (RAG), or AI agents is a plus. Knowledge of SQL and working with structured datasets.
Exposure to REST APIs and model deployment is a plus. Understanding Linux command line is an advantage.

Preferred Knowledge
Natural Language Processing (NLP) or Computer Vision fundamentals. Understanding of model fine-tuning and transfer learning concepts.
Awareness of AI ethics, responsible AI, and data privacy principles.
Soft Skills
Strong problem-solving and critical thinking abilities.
Curiosity and passion for AI research and emerging technologies.
Ability to work independently as well as in a collaborative team environment. Good documentation and technical writing skills.
Ability to conduct experiments, analyze results, and communicate findings effectively. Time management and willingness to take ownership of assigned tasks.