About AIRMO
AIRMO is a European climate-tech company using space and airborne technologies to monitor greenhouse gas emissions globally. Our instruments — combining LiDAR and hyperspectral imaging — detect and quantify methane and CO₂ emissions from industrial sites, pipelines, and national infrastructure.
We’re building a global monitoring system from air to space, helping energy companies, governments, and investors take real action on climate impact.
Role Overview
We are looking for an end-to-end Earth Observation (EO) Specialist with deep expertise in remote sensing, ML-based analytics, and data fusion to help advance AIRMO’s global methane and greenhouse gas monitoring capabilities. As part of our core science and data team, you will design, prototype, and operationalize state-of-the-art EO processing pipelines, from raw satellite data acquisition to fused, validated, and production-ready insights powering our Global Insights platform. You will contribute directly to a mission with global impact, helping bring transparency and accountability to global emissions.
Your Responsibilities in AIRMO
- Develop end-to-end EO processing pipelines, including ingestion, calibration, atmospheric correction, fusion, and validation workflows
- Work with multi-sensor datasets (e.g., hyperspectral, multispectral, SAR, thermal) and fuse them into robust, high-confidence methane and other GHG detection products
- Apply machine learning and advanced signal processing techniques to improve detection accuracy, reduce false positives, and enhance trace gas retrieval
- Translate research-grade algorithms into optimized, scalable, and production-ready pipelines
- Closely collaborate with software development and scientific teams to integrate outputs into APIs, dashboards, and customer-facing products
- Lead experiments, benchmarking, and model evaluations using real-world datasets
- Push the state of the art in EO research, satellite mission capabilities, and data fusion methodologies
- Contribute to publications, internal documentation, and technical discussions on scientific roadmap and architecture decisions
What you should bring to AIRMO
The ideal candidate will have:
- PhD in Remote Sensing, Earth Observation, Geoinformatics, Atmospheric Science, or a related field
- Proven experience with satellite-based methane or trace-gas retrievals, or related experience in EO analytics
- Hands-on expertise with machine learning, preferably for EO or geospatial applications
- Experience building data fusion workflows involving hyperspectral datasets
- Proficiency in Python and common EO/ML libraries
- Familiarity with Copernicus, NASA or commercial EO mission datasets
- Experience bringing research algorithms toward operational or production-grade pipelines
- Strong analytical mindset, scientific rigor, and ability to work in a multidisciplinary engineering environment
Nice to have
- Publications or conference contributions in remote sensing or ML
- Experience with GCP or other cloud environments
- Experience with atmospheric correction, radiative transfer models, or trace gas retrieval algorithms
What We Offer
- A chance to shape how climate and space technology is communicated globally
- Direct exposure to founders, investors, and international customers
- Flexible working hours and hybrid setup
- A mission-driven, curious, and slightly space-obsessed team