Senior AI/ML Engineer (Singapore, Indonesia, or India)

CDAH Platform Overview - The CDAH will be a cloud-native, open-source “operating system” for integrated climate and health intelligence, built on five pillars:

• AI R&D environment: Ingests multi-modal climate, environmental, epidemiological and socio-demographic data into a unified data lake & feature store; supports Kubeflow/PyTorch/TensorFlow pipelines with MLflow registry, automated benchmarking, architecture search, transfer learning and uncertainty-aware modeling. 
• Digital tool marketplace & public goods registry: User-facing portal for dashboards, mobile apps and alerting platforms; structured backend registry of pre-trained model packages, microservices, ETL scripts, governance adapters, metadata and version history. 
• Systems integration & deployment layer: Middleware adapters and Kafka messaging to plug AI services into DHIS2, HMIS, IDSR and similar platforms; Terraform/Ansible IaC, identity management, end-to-end encryption and compliance with data-governance standards. 
• Training environment: Web portal and virtual bootcamp infrastructure hosting open-access modules, instructor-led sessions, hands-on Jupyter labs, code templates and certification tracks on climate-health AI workflows and interoperability. 
• Real-world evaluation sandbox: Controlled simulation environment replicating public-health workflows, climate variability and institutional constraints; structured feedback loops for piloting, validating and refining tools prior to full-scale rollout. 

What You’ll Do

• Own the AI/ML roadmap: Drive end-to-end design, training, and deployment of models that fuse climate, environmental and health data to generate predictive analytics for early warning and strategic decision support across diverse climate-driven health challenges– leveraging transfer learning, uncertainty quantification, spatiotemporal neural architectures, and domain adaptation. 
• Package and validate model services: Containerize inference microservices, write unit/integration tests, and manage model-serving APIs. 
• Collaborate on CI/CD: Work with the Systems Architect to integrate models into the shared CI/CD pipeline; focus on model pipeline handoff and deployment validation. 
• Automated model testing and monitoring: Develop model unit tests, integration tests, and continuous drift/bias monitoring. 
• Integrate with national information systems: Develop and maintain middleware adapters to seamlessly plug AI services into DHIS2, HMIS, IDSR, and/ or other existing health information platforms– adhering to data-governance, security, and interoperability standards. Lead the model-serving middleware, while the Systems Architect leads the API Gateway. 
• Collaborate & consult: Partner with IMACS Data Scientist, Systems Architect, and in-country stakeholders to translate analytics into decision-support tools, technical roadmaps, and clear implementation guides. Serve as the primary AI/ML consultant for government and NGO clients. 
• Accelerate capacity building: Design and deliver modular training assets– Jupyter notebooks, code labs, technical playbooks– and co-facilitate virtual bootcamps, “office hours,” and hands-on mentoring for public health actors. 
• Innovate continuously: Lead research sprints in our R&D environment: evaluate emerging open-source AI frameworks, pilot agentic AI systems, and iterate on model performance using real-world climate and epidemiological datasets. 

What We’re Looking For

• Deep technical expertise:10+ years in AI/ML engineering, with a strong track record in deep learning, NLP, computer vision, or generative AI at scale. 
• Foundation Model mastery: Hands-on experience building, fine-tuning, and benchmarking large-scale transformer and multi-modal architectures (e.g., GPT, LLaMA, stable diffusion variants). 
• MLOps & Cloud proficiency:Expertise in Docker, Kubernetes, CI/CD (GitOps), and GPU-accelerated training on AWS, Azure, or GCP. 
• API & microservices: Proven ability to design, implement, and secure RESTful APIs and microservice ecosystems. 
• Consulting acumen: Exceptional stakeholder management, technical storytelling, and client-facing presentation skills– ideally honed at a top-tier consulting firm or tech organization. 
• Autonomous delivery:Demonstratedcapacity to deliver complex projects end-to-end, navigate ambiguity, and deliver production-ready solutions with minimal oversight. 

Preferred Qualifications 

• Prior engagement in global health, One Health, or climate-health use cases. 
• Familiarity with data governance frameworks (e.g., GDPR, HIPAA) and cybersecurity best practices. 
• History of designing and delivering technical training or bootcamps. 
• Contributions to open-source digital public goods or curated marketplaces/registries. 

Why You’ll Love This Role 

• High-impact mission: Your work will directly strengthen early warning systems and resilience in climate-vulnerable regions. 
• Technical leadership: Shape the AI/ML strategy for a pioneering global platform with full ownership of critical deliverables. 
• Innovation-friendlyenvironment: Experiment with state-of-the-art generative and agentic AI in a cloud-native R&D playground. 
• Global collaboration: Engage a diverse network of public-health experts, policymakers, and open-source communities.