AI ML Model Development:

·        Execute PoCs and MVPs for AI and ML projects, focusing on practical implementation.

·        Develop and refine ML models, including supervised and unsupervised learning algorithms.

·        Build and deploy GenAI solutions, such as Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) systems, and chatbots.

·        Collaborate with AI Engineers to integrate models into enterprise applications. Data Handling Preprocessing:

·        Collect, clean, and preprocess data to ensure quality inputs for model training.

·        Conduct exploratory data analysis (EDA) to uncover insights and inform model development.

·        Work with Data Engineers to ensure smooth data pipelines and infrastructure.

Model Evaluation Optimization:

·        Evaluate model performance using appropriate metrics and fine-tune algorithms for optimal results.

·        Monitor GenAI outputs for issues such as bias, hallucinations, and accuracy.

·        Implement feedback loops for continuous model improvement.

Collaboration Documentation:

·        Work closely with the AI Lead and cross-functional teams to align projects with business objectives.

·        Document model development processes, code, and findings for transparency and reproducibility.