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Artificial Intelligence (AI) Internship

Vunoh Global Services Ltd, “Vunoh Global” connects the diaspora to Kenya and Kenyans to global career and education opportunities, so efficiently it feels as good as being there. For diaspora services we offer errand services, investments advisory, real estate and legal services.

For those seeking opportunities abroad, we work closely with clients to explore and pursue international career, business and education pathways. Vunoh bridges the gap between Kenya and the world by enabling secure, convenient, and trustworthy cross-border interactions. Our values - Efficiency, Transparency, Accountability, Integrity, Reliability, Innovation, and Excellence define how we design our services, serve our clients, and build lasting trust.

The AI interns will design and deploy AI agents that handle real workflows such as investment research pipelines, financial reporting automation, cross-border transaction intelligence, and internal productivity systems that the whole team relies on. The intern will be at the centre of Vunoh's technology capability making operations and services faster, more intelligent, and reliable. They will work directly on machine learning models, AI-powered applications, and data pipelines that touch every part of the business while building a solid base that is transferable to multiple businesses and meeting a variety of needs.

As  "AI-first" practitioners and not just users of AI tools, the interns will be builders of the tools carefully connecting architecture level to the business user. Over 12 structured weeks, the interns move from foundations through applied AI to a fully presented capstone project, graduating as job-ready AI practitioners with a portfolio of real work.

Responsibilities

1. Build, train, and evaluate machine learning models on real business datasets across service lines including investments, real estate and other services;
2. Develop AI-powered applications using Python, FastAPI, and Streamlit that automate and enhance company internal workflows and client-facing services;
3. 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;
4. Conduct exploratory data analysis and produce clear, actionable data insights that inform business decisions across the organisation;
5. Apply prompt engineering techniques to build reliable, structured AI pipelines for content generation, classification, and summarisation tasks;
6. Package and deploy models using MLOps best practices including experiment tracking with MLflow, containerisation with Docker, and CI/CD pipelines with GitHub Actions;
7. Conduct responsible AI audits on models assessing for bias, fairness, explainability, and data privacy compliance;
8. Collaborate with the Product and Operations teams to identify AI automation opportunities and translate them into working prototypes;
9. Document all models, pipelines, and applications to professional standards including model cards, data cards, and technical READMEs;
10. Scope, build, and present a capstone AI project that solves a real problem
11. Any other duties as may be assigned from time to time.

Requirements

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

Learning Opportunities

By the end of this internship, the interns will have gained end-to-end exposure to machine learning model building and evaluation; exploratory data analysis and feature engineering on real business datasets, AI application development using FastAPI and Streamlit, prompt engineering and large language model integration via commercial APIs, MLOps including experiment tracking, Docker containerisation, and CI/CD pipelines; responsible AI auditing covering bias detection, explainability using SHAP, and fairness metrics, AI product strategy including use case scoping and product brief writing; and full capstone project development and live panel presentation.

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