Kigali, Rwanda, Rwanda On-site

Irembo Ltd is hiring a Machine Learning Engineer

Irembo Ltd is looking for a Machine Learning Engineer to design and deploy AI solutions that support our digital health services, with a focus on telemedicine. You will work across the end-to-end machine learning lifecycle, with a key focus on localizing and optimizing AI models for the Kinyarwanda language and local medical context. Your work will enable scalable AI solutions that expand healthcare access and strengthen our telemedicine impact.

What You'll Do

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

What We're Looking For

  • 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.
  • Demonstrated ability to work independently and deliver high-impact results under a tight contract timeline.

Nice to Have

  • 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.

Technical Stack

  • Python
  • TensorFlow
  • PyTorch
  • MLflow
  • Kubeflow
  • Docker
  • Kubernetes

Work Mode

This is an onsite position located in Kigali, Rwanda.

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.

Required Skills
PythonTensorFlowPyTorchMLflowKubeflowDockerKubernetesNatural Language Processing (NLP)Speech RecognitionSpeech SynthesisMLOpsFeature EngineeringModel Deployment PythonTensorFlowPyTorchMLflowKubeflowDockerKubernetesNatural Language Processing (NLP)Speech RecognitionSpeech SynthesisMLOpsFeature EngineeringModel Deployment
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About company
Irembo Ltd
A technology company that designs and develops digital products to ease the accessibility of services in users’ everyday lives worldwide, starting with Rwanda. Its pioneer products, IremboGov and IremboPay, are one-stop-shop e-governance and payment platforms.
All jobs at Irembo Ltd Visit website
Job Details
Department Data and Analytics
Category data
Posted 2 months ago