Artificial Intelligence (AI) Internship at Cytonn Investments

Responsibilities

• Build, train, and evaluate machine learning models on real business datasets across service lines including investments, real estate and other services;
• Develop AI-powered applications using Python, FastAPI, and Streamlit that automate and enhance company internal workflows and client-facing services;
• Integrate and work with commercial AI APIs including OpenAI and HuggingFace to build intelligent features such as smart document processing, digital investments, client query handling, next-gen AI-powered digital marketing and recommendation systems;
• Conduct exploratory data analysis and produce clear, actionable data insights that inform business decisions across the organisation;
• Apply prompt engineering techniques to build reliable, structured AI pipelines for content generation, classification, and summarisation tasks;
• Package and deploy models using MLOps best practices including experiment tracking with MLflow, containerisation with Docker, and CI/CD pipelines with GitHub Actions;
• Conduct responsible AI audits on models assessing for bias, fairness, explainability, and data privacy compliance;
• Collaborate with the Product and Operations teams to identify AI automation opportunities and translate them into working prototypes;
• Document all models, pipelines, and applications to professional standards including model cards, data cards, and technical READMEs;
• Scope, build, and present a capstone AI project that solves a real problem
• Any other duties as may be assigned from time to time.

Requirements

• Bachelor's degree in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field from a recognised university;
• Must have attained a B and above in KCSE or equivalent;
• Proficiency in Python or a clearly demonstrated ability to learn programming rapidly and independently;
• Tech-savvy mindset with demonstrable experience using AI tools such as ChatGPT or Gemini for research, analysis, or content tasks;
• Demonstrated interest in AI exemplified by actual prior project;
• Strong analytical and problem-solving skills with high attention to detail;
• Familiarity with data analysis, basic statistics, or machine learning concepts is an advantage;
• A team player willing to learn, adapt, and work with minimum supervision;
• Excellent organisation, communication, and interpersonal skills; and
• High levels of energy and enthusiasm with the ability to work under pressure and meet deadlines.