Earth Systems AI Lead Scientist
Location: Remote, Africa
Full Time
About the Startup
We are an early-stage, Africa-based, remote-first stealth startup developing physics- and science-informed AI systems to address complex scientific and environmental challenges. At the very start of our journey, we are laying the foundations for tools that combine advanced computational methods, spatial intelligence, and data-driven modeling to generate actionable insights across scientific and environmental domains.
Our approach is mission-driven, focusing on applying rigorous scientific methods and AI/ML to environmental and climate challenges in Africa. We cultivate a collaborative, multidisciplinary culture that values careful experimentation, curiosity, and practical impact.
Our team is remote-first across Africa, allowing talented individuals to contribute from anywhere on the continent while participating in a community committed to innovation, learning, and meaningful scientific impact.
Core principles and benefits of working with us include:
- Mission-driven impact: Contribute to initiatives that apply rigorous science and AI/ML to strengthen environmental and climate understanding across Africa
- Flexible, remote work: Collaborate with an Africa-based team from anywhere on the continent
- Growth Opportunity: Access to professional learning platforms and resources for continuous skill development
- Collaborative culture: Join a multidisciplinary, values-aligned team operating at the intersection of science, technology, and social impact
- Highly competitive compensation and equity options: Receive packages that reflect your expertise and contributions, with the potential to gain equity in the company
- Access to cloud services, latest development tools, and freedom to experiment
Role Overview
The Earth Systems AI Lead Scientist will lead the scientific and technical design of next-generation physics-informed ML models for African climate and environmental systems—spanning weather prediction, hydrology, atmosphere–land interactions, and environmental forecasting.
Key Responsibilities
- Lead design and development of physics-informed ML models (PINNs, FNOs, operator learning, PDE-constrained models)
- Define scientific architecture ensuring physical consistency, numerical correctness, and robust validation
- Collaborate with geospatial and data engineering teams to integrate high-quality datasets (satellite, reanalysis, sensor)
- Conduct and publish research in open, reproducible ways—papers, technical reports, datasets
- Lead benchmarking, error analysis, and stress-testing of models
- Contribute to open-source tooling advancing scientific ML for Africa
- Mentor ML engineers and junior scientists on scientific rigor and model design
Requirements
- MSc/PhD in Atmospheric Science, Earth System Science, Climate Science, Applied Mathematics, or Physics
- 5+ years of experience in climate modeling, numerical modeling, or Earth system ML
- Strong ML background: PDE-based models, operator learning, physics-informed neural networks
- Proficiency with PyTorch or JAX, scientific computing libraries, and numerical simulation tools
- Experience with satellite or reanalysis datasets
- Comfortable communicating in English, both written and verbal
Preferred
- Published research in climate ML, PINNs, operator learning, or numerical modeling
- Experience working with HPC clusters or cloud GPU systems
- Participation in open-source climate or ML projects
- Strong data storytelling and scientific communication skills
To apply, please complete and submit your application using this form.
Desired Skills
How to Apply
Find more details here https://www.notion.so/Geospatial-Remote-Sensing-Engineer-2b38d7ddd33580a7b205d59cb0a5528a
