Vacancy title:
AI/ML Expert

[Type: FULL_TIME, Industry: , Category: Computer & IT]

Jobs at:
Rwanda Revenue Authority

Deadline of this Job:
Friday, October 3 2025

Duty Station:
Rwanda | Kigali | Rwanda

Summary
Date Posted: Monday, September 29 2025, Base Salary: Not Disclosed

Similar Jobs in Rwanda
Learn more about Rwanda Revenue Authority
Rwanda Revenue Authority jobs in Rwanda

JOB DETAILS:

The Rwanda Revenue Authority (RRA) is committed to leveraging advanced data analytics, artificial intelligence (AI), and machine learning (ML) to improve taxpayer compliance, enhance service delivery, and optimize revenue collection. As part of this strategic initiative, RRA seeks to engage an AI/ML Expert with expertise in developing and deploying AI/ML models in operational environments, particularly within tax administration contexts.

The primary objective of this assignment is to provide hands-on technical support in the design, development, testing, and deployment of AI/ML solutions, and to ensure that RRA’s infrastructure, strategy, and governance frameworks are ready for sustainable AI/ML adoption.

Specific objectives include:
✓ Develop and deploy AI/ML models for priority tax administration use cases.
✓ Assess and recommend improvements to RRA’s IT infrastructure for AI/ML readiness.
✓ Review and refine the RRA Data Science Strategy and Data Governance Framework to ensure completeness, alignment with best practices, and readiness for implementation.

3. Scope of Work

The expert will be responsible for:

A. AI/ML Solution Development
✓ Needs Assessment & Solution Design: Review RRA’s data sources, systems, and analytical capabilities; identify AI/ML opportunities aligned with RRA’s strategic priorities; propose AI/ML models and solutions tailored for tax administration use cases.
✓ Model Development & Testing: Clean, preprocess, and structure datasets for ML training and testing; select appropriate algorithms and evaluation metrics; train, validate, and optimize AI/ML models.
✓ Deployment & Integration: Deploy models into RRA’s operational environment; integrate AI/ML outputs with existing tax administration systems; ensure model performance monitoring and maintenance.
✓ Capacity Building: Provide on-the-job training for RRA data scientists and analysts; document methodologies, workflows, and deployment processes; support creation of reusable AI/ML development templates and best practices.

B. Infrastructure Readiness Assessment
✓ Conduct a comprehensive review of RRA’s IT infrastructure, including data storage, processing capacity, cloud readiness, and security controls, to determine suitability for AI/ML workloads.
✓ Identify infrastructure gaps and recommend upgrades or new solutions to support large-scale AI/ML deployment and integration.
✓ Provide a roadmap for infrastructure scaling in line with anticipated AI/ML demands.

C. Strategic & Governance Review
✓ Review and refine the RRA Data Science Strategy to ensure it is aligned with international best practices, emerging AI/ML trends, and RRA’s operational needs.
✓ Review and refine the Data Governance Framework to assess completeness, effectiveness, and readiness for implementation.
✓ Recommend enhancements to ensure robust data quality management, privacy compliance, and secure AI/ML operations.

4. Deliverables

✓ Inception report with detailed work plan and AI/ML opportunities assessment.
✓ IT infrastructure readiness assessment report with recommendations and upgrade roadmap.
✓ Revised and validated Data Science Strategy and Data Governance Framework documents.
✓ At least two fully functional AI/ML models deployed in production.
✓ Documentation of model development and deployment procedures.
✓ Capacity-building workshops for RRA staff.
✓ Final consultancy report summarizing outcomes, lessons learned, and recommendations.

5. Required qualifications skills and competence

✓ Advanced Degree in Data Science, Computer Science, Artificial Intelligence, or related field.
✓ Minimum 5 years of hands-on experience in AI/ML model development and deployment.
✓ Proven experience in infrastructure assessment and technology road mapping for AI/ML readiness.
✓ Expert in Python with strong knowledge of libraries such as NumPy, pandas, scipy, and Scikit-learn, and familiarity with software development best practices including version control (Git), testing, and packaging.
✓ Expertise with distributed computing tools (Apache Spark, Dask, Hadoop), cloud platforms (AWS, GCP, Azure ML services), and handling millions or billions of records efficiently.
✓ Familiarity with CI/CD for ML pipelines, model monitoring, versioning, and deployment using tools such as FastAPI/Flask , MLflow, Kubeflow, Airflow, Docker, and Kubernetes
✓ Strong experience with text preprocessing, embeddings (Word2Vec, GloVe, BERT), large language models (GPT, LLaMA, etc.), prompt engineering, and frameworks such as Hugging Face Transformers, LangChain, and OpenAI API
✓ Expertise in machine learning and neural networks, including feedforward networks, CNNs (computer vision), RNNs/LSTMs/Transformers (time series, NLP), transfer learning, and fine-tuning large models, using frameworks such as TensorFlow, PyTorch, and Keras.
✓ Proficiency in testing frameworks (pytest, unittest), code formatting and linting tools (black, isort, flake8), interactive coding and notebooks (Jupyter, IPython), API interaction (requests, aiohttp), and web scraping/parsing libraries (BeautifulSoup4, lxml, Scrapy).
✓ Strong understanding of data governance, data management, and AI ethics.
✓ Excellent communication and capacity-building skills.

Work Hours: 8

Experience in Months: 60

Level of Education: bachelor degree

Job application procedure
Interested in applying for this job? Click here to submit your application now.

All Jobs | QUICK ALERT SUBSCRIPTION