Machine Learning Engineer

Irembo is a technology company that designs and develops digital products to ease the accessibility of services in users’ everyday lives worldwide, starting with Rwanda. Our pioneer products, IremboGov and IremboPay, have enabled Rwandan citizens and foreigners to access and pay for over 150 public services online through our one-stop-shop e-governance and payment platforms. To date, we have facilitated over 30 million transactions through our platforms and have ambitious goals to scale our technology worldwide to enable more governments and institutions to serve their citizens better. More information is available on irembo.com.

Our flagship platforms, IremboGov and IremboPay, have transformed how government services are accessed and paid for, proving our ability to simplify complex processes and enhance public engagement.

We are now bringing the same innovation to healthcare to ensure every Rwandan has access to efficient, high-quality digital health services. Building on the legacy of Babyl Rwanda, which introduced telemedicine in 2016 and delivered over 3.5 million consultations in seven years through USSD and voice calls, and was integrated with health facilities for diagnostics, prescriptions, and referrals.

Our first step is the launch of a national-scale telemedicine platform, designed to expand access and convenience, enabling services that can only be better delivered via telemedicine, such as remote consultations, chronic disease management, and preventive care follow-ups. It also sets a new paradigm for healthcare delivery by leveraging advanced technologies, including AI, to improve diagnosis, personalize care, and optimize health system efficiency.

Location: Kigali, Rwanda (On-site)

Duration: 24 Months (Fixed Term)

Terms of Reference: Machine Learning Engineer

The Opportunity 

We are looking for a skilled Machine Learning Engineer to help design and deploy AI solutions that support Irembo’s digital health services. In this role, you will contribute to building intelligent systems that enhance remote healthcare delivery, improve clinical decision support, and help generate insights from health data to strengthen service delivery.

You will work across the end-to-end machine learning lifecycle, including designing and developing models, improving existing systems, and building reliable training and deployment pipelines. A key focus of this role will be the localization and optimization of AI models to ensure they perform effectively in the local context, including strong support for the Kinyarwanda language.

The ideal candidate will have experience building machine learning models from scratch, refining and scaling existing solutions, and ensuring reliable deployment in production environments. Through this work, you will help enable scalable AI solutions that expand access to healthcare and strengthen the impact of telemedicine services.

Key Responsibilities: 

• Model Design & Development: Design, develop, and implement machine learning models tailored to telemedicine, including patient triage, symptom assessment, and clinical decision support.
• Model Localization: Fine-tune models to support Kinyarwanda and accurately capture local medical context for better patient outcomes.
• Model Optimization: Refine and enhance existing models for accuracy, efficiency, scalability, and reliability in production.
• Data Pipeline Management: Collaborate with Data Engineers to build robust pipelines for ingestion, cleaning, feature engineering, and labeling of anonymized clinical data.
• Experimentation & Evaluation: Plan and execute training experiments, hyperparameter tuning, and rigorous evaluation of model performance, bias, and clinical relevance.
• Deployment & MLOps: Deploy models into production environments and maintain MLOps infrastructure for CI/CD, model versioning, monitoring, and drift detection.
• Integration: Work with Software Engineers to integrate model outputs securely and efficiently into telemedicine platforms through APIs.
• Responsible AI Practices: Ensure all models and processes comply with data privacy, security, and ethical standards, particularly when handling sensitive health data.

Qualifications: 

Required Skills & Experience:

• Minimum of 3+ years of hands-on experience as an ML Engineer or AI Developer working on production systems.
• Expert proficiency in Python and deep experience with major ML/Deep Learning frameworks (e.g., TensorFlow, PyTorch).
• Solid background in relevant AI domains, specifically Natural Language Processing (NLP) and/or Speech Recognition/Synthesis.
• Proven ability to manage the entire ML lifecycle, from data preparation and feature engineering to training, optimization, and production deployment.
• Experience with MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes) for model scaling.
• Knowledge of healthcare or telemedicine applications is highly desirable.
• Contract Focus: Demonstrated ability to work independently and deliver high-impact results under a tight contract timeline.

Preferred Skills

• Master's degree or Ph.D. in Computer Science, Machine Learning, or a related quantitative field.
• Experience with Large Language Models (LLMs) and techniques like transfer learning or fine-tuning.
• Familiarity with compliance standards for government or public-sector technology.
• Experience with Voice/Speech models.
• Experience working with low-resource languages.

Why Join This Project?

You will solve the critical challenge of making AI accessible in local languages, ensuring equitable access to advanced health technology.

Please note that the salary for this position is commensurate with experience and qualifications and will be discussed during the interview process. 

Application Deadline

• March 16, 2026

We are an equal opportunity employer and are committed to providing a positive interview experience for every candidate. We're on a mission to change our continent through technology and are committed to a diverse and inclusive workplace and strongly encourage applicants from all backgrounds, nationalities, and walks of life.

Our head office is based in Kigali, Rwanda.