AI & Machine Learning Specialist, Data-Activated Architecture for Resilient Transition (DART)

AI & Machine Learning Specialist, Uganda Data-Activated Architecture for Resilient Transition (DART)

About Palladium:

Operating in over 50 countries, Palladium is a global consulting and implementation company working in partnership with governments, businesses, investors, and communities to design and deliver solutions that create lasting positive impact. We address some of the world’s most complex challenges across infrastructure, economic growth and natural capital, health, energy, climate and environment, and digital transformation—strengthening systems, institutions, and markets to support inclusive and sustainable development. Our more than 2,100 staff worldwide work as trusted advisors across diverse contexts, combining deep technical expertise, implementation techniques, and innovative technology to deliver locally informed, client-focused solutions that help organizations achieve measurable, sustainable impact.

Palladium is part of GISI’s global family of companies, which aims to create solutions for the world’s most complex challenges. With annual revenues of $14 billion, GISI’s approximately 15,000 employees are engaged in projects across 100 countries worldwide providing construction, program/project management, and engineering consulting services.

Project Background:

Data-Activated Architecture for Resilient Transition (DART) supports the Ministry of Health (MOH) to strengthen and scale interoperable, fit-for-purpose digital health systems. The project supports facility digitization and EMR readiness; National Data Warehouse (NDWH) stabilization; data-center design and cybersecurity; Health Information Exchange (HIE) operations and priority integrations; workforce certification; survey modernization; responsible AI adoption; and service-delivery data reporting performance. The project is designed to build on MOH-owned systems, repositories, standards, and governance structures, with progressive transfer of capability to government and Ugandan institutions. Project period is anticipated 2026–2030, beginning with a six-month foundation phase.

Note: All positions are subject to award, final organizational design, and Palladium hiring procedures. Reporting lines may be adjusted during mobilization. “MOH” includes the responsible Directorate/Department of Health Informatics (DHI) and other government units as applicable.

Position Summary:

The AI & Machine Learning Specialist supports MOH/DHI to develop and validate a practical national AI implementation framework and implement two approved priority AI use cases on existing government-supported platforms. The position ensures AI activities are responsible, useful, technically sound, monitored, and aligned with MOH governance, data protection, and national digital health priorities.

Location:

This role and project will be based out of Kampala, Uganda with national and regional travel as required.

Reporting and Supervision:

• This role will report to the Technical Director, Interoperability & HIE Architect, DART

Primary Responsibilities:

• Support development of an MOH-owned AI implementation framework, including use-case intake, risk classification, data-governance requirements, validation criteria, approval pathways, monitoring requirements, and escalation procedures
• Design, develop, validate, and document approved AI use cases, including DHIS2 data-entry anomaly detection and AI-enabled acoustic screening for respiratory disease or other MOH-approved priorities
• Work with data engineering, interoperability, cybersecurity, clinical, and program teams to ensure AI use cases use approved data sources, secure environments, and documented data pipelines
• Develop model-development, testing, evaluation, bias assessment, performance-monitoring, versioning, and retraining procedures
• Ensure human oversight, auditability, privacy protection, and appropriate use of de-identified or authorized data
• Support user testing, workflow integration, training, post-deployment monitoring, and decision thresholds for AI-enabled tools
• Document technical methods, model limitations, validation evidence, user guidance, and governance decisions for MOH review
• Build capacity of MOH and Ugandan technical teams in responsible AI concepts, implementation practices, and ongoing model monitoring

Qualifications and Experience:

• Master’s degree in data science, computer science, artificial intelligence, statistics, biomedical engineering, health informatics, or related field
• At least 5 years of experience in machine learning, data science, predictive analytics, or AI product development
• Demonstrated skills in Python, machine learning frameworks, model evaluation, data engineering, and data visualization
• Experience applying AI or analytics in health, public health, or low-resource settings is strongly preferred
• Knowledge of responsible AI, privacy, bias assessment, human-centered design, and model monitoring
• Strong technical documentation, stakeholder engagement, and English communication skills

Applications will be accepted on a rolling basis. We encourage you to apply early as the position may close once a suitable candidate is found. Please note that only shortlisted candidates will be contacted.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or status as a protected veteran.

Should you require any adjustments or accommodations to be made due to a disability or you are a neurodivergent individual, or for any other circumstance, please email our team at accessibility@thepalladiumgroup.com and we will be in touch to discuss.

Safeguarding - We define Safeguarding as “the preventative action taken by Palladium to protect our people, clients and the communities we work with from harm”. We are committed to ensuring that all children and adults who come into contact with Palladium are treated with respect and are free from abuse. All successful candidates will be subject to an enhanced selection process including safeguarding-focused interviews and a rigorous due diligence process.