As a Geospatial AI Engineer at Samudra Oceans Limited, you will build ML functions fusing satellite remote sensing data with in-situ sensor measurements. You’ll own the geospatial AI pipeline end-to-end, creating analytics that transform 50TB+ of proprietary data into actionable intelligence for global customers across the maritime and energy sectors.
Geospatial AI Engineer at Samudra Oceans Limited
Samudra Oceans Limited is revolutionizing the blue economy by replacing slow, expensive research vessels with real-time AI intelligence. Backed by the European Space Agency and winners of the EarthShot Prize, they are seeking a Geospatial AI Engineer to fuse satellite data with proprietary sensor measurements. You will own the ML pipeline for a 50TB+ dataset, building production-ready features that monitor the world's oceans. If you're an expert in Python and remote sensing looking for a high-impact climate tech role with £90k salary and equity, this is your chance to build the future of ocean intelligence.
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Location
London, United Kingdom
Compensation
£90k + Equity
Company
Samudra Oceans Limited
Role overview
Samudra Oceans Limited (SamudraOceans) is a London-based blue-tech and climate-tech company building an end-to-end ocean intelligence platform that combines marine-edge robotics, IoT sensing, and AI to deliver real-time, scalable monitoring of coastal and offshore environments.[1][6] Its systems use autonomous, ocean-grade hardware and static monitoring robots equipped with advanced sensors and cameras to continuously measure over 15 ocean parameters such as temperature, salinity, pH, dissolved oxygen, turbidity, and biodiversity, turning ocean data into actionable insights for ports, harbours, aquaculture, and marine conservation.[1][6][12] The company focuses on scaling sustainable, mega-scale seaweed farming and traceable blue-carbon projects, using robotics and AI to enhance seaweed farm efficiency, predict yield, detect pathogens, and monitor nutrient and acidity levels, thereby supporting coastal communities, biodiversity, and the wider blue economy.[4][7][8][12][13] Through AI-powered analytics and machine learning models trained on proprietary time-series data, Samudra Oceans provides predictive alerts for storms, biofouling, environmental compliance, and operational risks, along with real-time dashboards, API access, and automated reporting so enterprises can integrate ocean intelligence into operations, risk models, and decision-making workflows.[1][6][8][12] Operating projects in the UK, Scotland, Jamaica and expanding to India and Sri Lanka, the company positions the ocean as a key pathway for climate action and aims to remove large-scale atmospheric carbon via seaweed-based blue carbon initiatives.[7][12][13]
What you will do
- Fuse satellite remote sensing data with ground-truth sensor measurements to benchmark and validate ocean parameters on the NIRA dashboard platform.
- Build and deploy automated anomaly detection and geospatial analytics tools into a production environment, moving models from notebooks to live features.
- Own the end-to-end geospatial AI pipeline, from raw data processing to developing the ML functions that power real-time operational alerts for customers.
Who this is a fit for
- Strong background in satellite remote sensing and geospatial analysis using industry-standard libraries such as GDAL, rasterio, xarray, or Google Earth Engine.
- Proven experience as a Production ML Engineer, with a track record of shipping models in a commercial product environment using Python.
- A startup-ready mindset with the ability to work across the full stack and navigate ambiguity while scaling ML capabilities from the ground up.
Why this role is remarkable
- Work with a unique 50TB+ proprietary ocean dataset that is impossible to replicate, providing a distinct competitive advantage in the blue economy.
- Join a high-impact climate tech startup that has won prestigious awards including the EarthShot Prize and the Wilkes Climate Prize.
- Directly influence the intelligence layer of ocean monitoring, moving beyond outdated research vessels to real-time, AI-driven compliance and operational insights.
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