Key skills
PythonAIMachine LearningMLNLPLLMPyTorchTensorFlowscikit-learnAnalyticsAWSAzureGoogle CloudLeadershipRisk Management
About this role
Job Title: AI for Development Specialist
Location: Remote
Location: Remote
Position Summary:
Senior AI and machine learning specialist responsible for developing, advising on, and overseeing AI and ML use cases tailored to development sector contexts. Focused on responsible AI, governance frameworks, and practical applications in low-resource and public-sector settings.
Engagement Details:
- Location: Home-based, remote. No office attendance required.
- Engagement type: Independent consultant or sub-contractor under company.
- Duration: Level of Effort basis per task order. Initial bench placement is for 12 months with extensions possible.
- Travel: Only when a specific task order requires it. All travel pre-approved and reimbursed.
Key Responsibilities:
- Develop AI and ML use cases, prototypes, and production models tailored to development contexts including health, education, agriculture, and crisis response.
- Build and supervise machine learning models, NLP systems, predictive analytics tools, and decision-support applications.
- Conduct AI readiness assessments and ethical risk assessments for country programs and donor-funded initiatives.
- Develop and apply AI governance frameworks aligned with NIST AI Risk Management Framework, OECD AI Principles, UNESCO Recommendation on the Ethics of AI, and emerging country-level guidance.
- Advise on responsible AI integration into service delivery, including bias detection, fairness evaluation, model monitoring, and human oversight design.
- Contribute technical content to proposals, concept notes, and thought leadership on AI in development.
Required Qualifications:
- Bachelor's degree required in Computer Science, Data Science, AI, or related field. Master's or PhD strongly preferred in AI, Machine Learning, Computer Science, or Data Science.
- Minimum 7 years of relevant professional experience, with 5 to 10 plus years specifically applying AI and ML in real-world environments.
- Demonstrated experience developing or supervising ML models, NLP systems, predictive analytics, or decision-support tools.
- Strong knowledge of AI governance, risk frameworks, and responsible AI methodologies.
- Proficiency with Python, common ML frameworks such as PyTorch, TensorFlow, scikit-learn, and modern LLM tooling.
- Experience in low and middle income countries or public sector environments preferred.
Preferred Certifications:
- CAP (Certified Analytics Professional)
- AI ethics certifications
- Azure AI Engineer, AWS Machine Learning Specialty, or Google Cloud Platform ML Engineer