Job Recruitments at African Population And Health Research Center (APHRC)

APHRC is seeking to recruit a Full Stack Developer, /s/he will enable robust, real-time AI functionality across DSP’s platforms while ensuring efficient data flow, model reliability, and system scalability. The appointment will be for a period of six (6) months.

KEY RESPONSIBILITIES:

The Full Stack Developer will support AI-driven initiatives such as Policy Lens AI, Data Science Without Borders (DSWB), and a No-Code Machine Learning Platform. The ideal candidate will have expertise in mobile app development, frontend/backend systems engineering, and cloud/DevOps infrastructure. The developer will ensure real-time AI functionality, efficient data flow, model reliability, and system scalability while addressing Africa’s evolving data ecosystem challenges, including secure data sharing and privacy protection:

• Develop, optimize, and maintain high-quality mobile and web applications.
• Ensure consistent, high-performance functionality across both iOS and Android platforms.
• Lead and collaborate in frontend development initiatives for web and mobile application projects.
• Build and maintain interactive and visually appealing analytics dashboards.
• Optimize frontend performance specifically for AI-integrated features.
• Design and implement reusable AI-powered UI components.
• Develop and manage robust backend services to support web application functionalities.
• Optimize database designs and query performance tailored for AI-driven applications.

Education Qualifications, Experience and Core Competencies

• Bachelor’s degree in data science, computer science, software Engineering human-computer interaction (HCI), or a related field with a strong UI/UX background.
• Two (2) years of experience in frontend and backend development, with at least one (1) year specifically in AI-driven user interfaces.
• Experience with No-Code/Low-Code ML platforms.
• Knowledge of AI ethics and responsible AI deployment.
• Expertise in React Native or Flutter for cross-platform mobile development.
• Mastery of React.js/Next.js or Vue.js/Svelte for dynamic web applications.
• Proficiency in state management tools (Redux, Zustand, Context API).
• Solid understanding of UI/UX design principles, particularly for data-heavy and AI-driven applications.
• Experience with UI/UX design using FIGMA or any other related tools.
• Experience developing chat interfaces, real-time analytics dashboards, and document processing UIs.
• Familiarity with Web Workers, Web Assembly (WASM), or TensorFlow.js.
• Proficient in fetching, caching, and streaming data from large language model (LLM) backends using APIs.
• Expertise in backend technologies, specifically Python (FastAPI, Django) or Node.js.
• Experience with WebSockets and Server-Sent Events (SSE).
• Advanced skills in CSS/SCSS, Tailwind CSS, or Material-UI.
• Knowledge of responsive and accessible design practices.
• Strong understanding of mobile architecture, performance optimization, and offline functionality.
• Proficiency in API development (REST/GRPC), WebSockets, and Graph QL
• Database expertise, particularly with PostgreSQL for data caching and synchronization.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Familiarity with continuous integration/continuous deployment (CI/CD) pipelines.
• Experience with cloud services on AWS, GCP, or Azure.
• Proven experience deploying mobile apps to Google Play Store and Apple App Store.
• Strong problem-solving abilities, particularly related to AI-driven UX/UI challenges.
• Passion for health-tech and AI-driven consumer applications.
• The ability to effectively translate complex AI workflows into intuitive user interfaces.
• Excellent teamwork and communication skills.

APHRC is seeking to recruit a Machine Learning/Data Engineer, s/he will develop and optimize the AI-powered applications, ensuring seamless integration of machine learning models and LLM APIs. The appointment will be for a period of six (6) months.

KEY RESPONSIBILITIES:

The Center operates on the principle that data is a public good and champions the Findable, Accessible, Interoperable, and Reusable (FAIR) principles of data management to facilitate secure, timely, and user-friendly data access and sharing, ensuring it is available to all authorized users. The Machine Learning specialist will bring essential competencies in mobile AI/ML integration, scalable backend systems, and cloud-native DevOps, positioning DSP at the forefront of AI innovation:

Education Qualifications, Experience and Core Competencies

• Integrate and deploy AI/ML models and LLMs within mobile and web applications.
• Develop, manage, and optimize Dockerized AI services.
• Ensure high availability, scalability, and security across cloud and on-prem systems.
• Automate and streamline CI/CD pipelines to facilitate seamless updates.
• Implement cost-monitoring and optimization strategies for cloud resources.
• Develop comprehensive disaster recovery plans for critical AI services.
• Maintain secure and efficient API interactions with AI models.
• Monitor, measure, and enhance API latency for real-time responsiveness.
• Document AI workflows and data pipelines to facilitate cross-team collaboration.
• Bachelor’s degree in computer science, Data Science, or a related field with specialization in AI/ML.
• Two (2) years of experience in DevOps/cloud roles, including at least one (1) year specifically dedicated to AI model deployment.
• Hands-on experience integrating ML models (TensorFlow Lite, ONNX, PyTorch) into mobile applications.
• Proficiency with Large Language Model (LLM) APIs such as OpenAI, DeepSeek, Claude, and Llama, including advanced prompt engineering techniques.
• Experience in building Retrieval-Augmented Generation (RAG) pipelines, fine-tuning, and developing agent-based systems.
• Strong familiarity with AI orchestration frameworks like LangChain, LlamaIndex, or AutoGen.
• Knowledge and practical experience with vector databases (FAISS, Chroma, Pinecone, Weaviate).
• Proficiency in Python data transformation tools, including pandas, NumPy, scikit-learn, and pyCaret.
• Familiarity with ML model deployment tools (MLflow, Seldon Core).
• Expertise with containerization technologies (Docker) and orchestration platforms (Kubernetes—EKS, GKE, AKS).
• Mastery of cloud services on AWS, GCP, Azure, or on-prem equivalents such as OpenStack.
• Strong experience in Infrastructure as Code (IaC) tools like Terraform, Ansible, or Pulumi.
• Proficient in setting up CI/CD pipelines using GitHub Actions, ArgoCD, or Jenkins.
• Familiarity with monitoring and logging solutions such as Prometheus, Grafana, and ELK Stack.
• Knowledge of model quantization and edge AI for efficient on-device inference.
• Experience with model serving platforms like TensorFlow Serving or Triton Inference Server.
• Competency in database scaling and management, specifically PostgreSQL/MySQL for AI workloads.
• Strong analytical skills to troubleshoot and solve deployment bottlenecks.
• Ability to manage and optimize cloud/on-prem infrastructure costs.
• Security-focused mindset to ensure robust, secure AI application deployments.
• Proven capability in designing scalable and efficient AI architectures.
• Excellent documentation and knowledge-sharing abilities.

The African Population and Health Research Center (APHRC) is a premier research-to-policy institution, generating evidence, strengthening research and related capacity in the African research and development ecosystem, and engaging policy to inform action on health and development. APHRC seeks to drive change by developing strong African research leadership and promoting evidence-informed decision-making (EIDM) across sub-Saharan Africa. APHRC seeks to recruit a Data Standards and FAIR Implementation Officer to lead the design, documentation, and implementation of data models and metadata workflows across the network in the Data Science Program (DSP).

DUTIES/RESPONSIBILITIES

The Data Science Without Borders (DSWB) project aims to strengthen the use of advanced data science tools in health across Africa through co-designed, locally led strategies. The initiative focuses on harmonizing data, implementing AI/ML tools, and promoting FAIR (Findable, Accessible, Interoperable, Reusable) data practices across partner institutions in Cameroon, Ethiopia, Senegal, and Kenya.

This role will drive technical leadership in deploying the OMOP Common Data Model (CDM), streamlining metadata workflows, and embedding FAIR (Findable, Accessible, Interoperable, and Reusable) data principles into practice. As a key contributor to the Data Science Without Borders (DSWB) project, this position will advance data harmonization, interoperability, and reuse across partner institutions, fostering collaboration and evidence-based insights. With the growing demand for standardized, high-quality data, the specialist will be instrumental in building robust data infrastructure, promoting consistent best practices, and enabling secure federated data sharing. By doing so, s/he will help establish scalable, sustainable data science ecosystems that empower research and decision-making across Africa.

Under the supervision of the DSWB Project Technical Lead and in collaboration with Pathfinder institution data teams, the incumbent will: –

• Design and implement data harmonization pipelines using OMOP CDM, Pentaho, and associated OHDSI tools.
• Develop and maintain machine-readable metadata workflows (e.g., Schema.org, DDI Lifecycle, JSON-LD).
• Lead the configuration of a FAIR-compliant data catalog that supports federated search and linked data integration.
• Standardize vocabularies and terminologies used in longitudinal and clinical health datasets.
• Support Pathfinder institutions in implementing ETL processes and reproducible research practices.
• Conduct capacity-building workshops and mentorship sessions on FAIR, metadata standards, and health data interoperability.
• Work with institutional data stewards to document FAIR Implementation Profiles and metadata schemas.
• Support the implementation of cloud-based collaborative analysis under the federation learning system.
• Contribute to collaborative publications and technical documentation.

Qualifications, Skills, and Experience

• A master’s degree in Epidemiology, Data Science, Health Informatics, or Information Technology.
• Minimum of five (5) years post first-degree experience in data management, data harmonization, and implementation of FAIR data principles within health research or related domains.
• Proven experience implementing FAIR data principles and using metadata standards like DDI, Schema.org.
• Proficiency with OMOP CDM, OHDSI tools (e.g., ATLAS, Achilles), and ETL processes.
• Strong command of R, Python, SQL, and visualization tools like Power BI, Apache Superset.
• Experience working with health surveillance, EHR data, or clinical research datasets.
• Record of peer-reviewed publications or technical documentation in relevant areas.
• Excellent communication and stakeholder engagement skills