Geospatial & Earth Data

Experts in Global Geospatial & Earth Data Recruitment

There’s never been a better time to work in Geospatial & Earth Data. From public nanosatellites to urban digital twins, a flurry of breakthroughs is changing the way we observe the world, and it’s leading to essential progress in disaster response, climate analysis, and resource management.

As one of the fastest-growing areas of deep tech, the industry is currently experiencing a spike in demand for talent.

Thanks to our community networks and specialised domain knowledge, our Geospatial & Earth Data division is well-positioned to support the unique hiring needs of today’s businesses.

Hire Incredible Geospatial & Earth Data Talent:

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Why Choose DeepRec.ai for Geospatial & Earth Data Recruitment?

We’ve built a dedicated division for Geospatial & Earth Data, led by specialists who live and breathe this domain.

With years of experience and an exceptional global network, our head of staffing brings a level of knowledge and credibility that ensures both clients and candidates are speaking to someone who understands their world.

Our expertise is backed by a global community network, supported by our presence in Boston, London, Berlin, Zurich, and Dublin, and our group reach of over 1.3 million people.

For Employers, This Means:

  • Reduced hiring risk. Our domain expertise, talent mobility support, and in-house compliance team ensure only qualified, relevant candidates reach you, cutting wasted time and mismatched hires.

  • Flexible workforce solutions that scale with your demand. DeepRec.ai provides a range of options that we can tailor to your unique needs: Embedded, Retained, Contingent, and Contract hiring models.

  • We build a consultative partnership and take time to understand your business goals, culture, and technical roadmap before advising on the best hiring strategies to meet them.

  • Rapid delivery. We fill permanent roles in an average of 30 days and contract positions in just one week, helping you avoid costly project delays.

For Candidates, This Means:

  • We can connect you with rare opportunities that never make it to the open market. Many of the best Geospatial jobs are secured through trusted networks long before they're advertised, and thanks to our position in the community, we can help you get a head start.

  • As part of Trinnovo Group, we're B Corp certified, a reflection of our commitment to responsible business and building diverse, inclusive communities. For professionals in Geospatial & Earth Data, it means working with a recruitment partner whose values align with the environmental and societal impact at the heart of your field.

  • We help you with more than introductions. From career positioning and salary benchmarks to interview prep and long-term planning, we’re here to support your growth.

  • We’re region-sensitive but globally connected. Offices in Boston, London, Berlin, Zurich, Dublin, and the USA make international opportunity accessible, while still being rooted in the local tech scenes you know best.

Behind all of this is our belief that careers grow stronger through community. The networks, events, and conversations you join through DeepRec.ai don’t just open doors to roles; they keep you connected to the ideas, people, and innovations shaping the future of Geospatial & Earth Data.

What We Mean by Community-Led Recruitment

When time is short and talent pools are shallow (as they nearly always are in Deep Tech), an alternative approach to recruitment is essential.

Since day one, we’ve been building a diverse, engaged, international deep tech community that creates easy access to a high-quality talent pool. Here’s how we’ve done it:

  • Global events programme: From our London-based Breakfast Bytes meetup to our Women in AI series in Berlin, we’ve created spaces to share ideas, make face-to-face connections, and learn from the pioneers leading the deep tech revolution.

  • Podcast series: We launched our new podcast series, Earth Observed, to platform voices from across the full spectrum of Geospatial & Earth Data. With weekly releases, we use DeepRec.ai’s reach to strengthen the online voice of the community.

  • Newsletters: Our monthly LinkedIn newsletters help keep the community engaged and up to date with the latest and greatest technological innovations.

  • Tech Enablement: We’ve invested heavily in our tech stack over the last few years, enabling us to lean on a market-leading candidate database to keep our community engaged. From automated sequencing to opportunity matching and diversity tracking, we’ve built a platform that makes every connection stronger.   

  • Insights Hub: Our centralised insights hub is the port of call for Deep Tech enthusiasts from around the world. Check it out here.

Earth Observed

Earth Observed is our new podcast series shaped by a shared fascination with our planet and the technology that transforms how we see it.

It's a space to hear from the people designing satellites, building geospatial platforms, and turning vast streams of Earth data into tools for understanding and improving life on the ground.

If you'd like to appear on the podcast, contact our Head of Staffing for Geospatial & Earth Data directly. We'd love to hear from you: sam.warwick@deeprec.ai 

The series is now available to stream live on Spotify and YouTube – take a look at the first episode below: 

GEOSPATIAL & EARTH DATA CONSULTANTS

Sam Warwick

Senior Consultant – Geospatial, Earth, & Defence Technology

LATEST JOBS

New York, United States
Machine Learning Engineer (NLP)
Machine Learning Engineer (NLP) About the Company This early-stage environmental intelligence startup is building next-generation AI systems that help global organisations understand and plan for water-related risks. Their platform combines deep learning with physics-based modelling to generate high-resolution insights for some of the world’s largest infrastructure operators, consumer brands, and investors. Backed by leading scientific minds across climate, hydrology, and machine learning, the company is now expanding its capabilities by developing a new social risk function that captures the human, regulatory, and community dynamics that shape water outcomes around the world.Why JoinJoin a team pushing the boundaries of environmental intelligence, combining physical and social risk modelling into a unified AI platform. Work with world-class researchers, publish meaningful science, and help deliver tools with tangible global impact.Pioneer a new capability: You’ll be the first ML engineer dedicated to modelling social, political, and reputational water risk.Cutting-edge work: Blend NLP, LLMs, graph intelligence, and geospatial modelling into a real, production platform.Genuine impact: Your models will inform global water stewardship decisions across high-risk regions.Interdisciplinary collaboration: Work alongside scientists and researchers across climate, hydrology, and social systems.Early-stage ownership: Build from first principles in a fast-moving, mission-driven startup with strong early traction.What You’ll DoBuild NLP, LLM, and multi-modal pipelines to analyse community, regulatory, media, and public-sentiment signals — including stance detection, topic/event clustering, and stakeholder network mapping.Fuse unstructured social data with geospatial and physical-risk datasets to generate unified risk insights for real-world decision-making.Partner with climate and domain scientists to translate social signals into actionable risk metrics, contributing to both product development and peer-reviewed research.Deploy scalable, interpretable ML systems into production via APIs and platform infrastructure.What You Bring3 years building applied ML/NLP systems, ideally across text, geospatial, or social-network data, including sentiment/stance modelling and multi-source pipelines.Strong Python plus experience with PyTorch/TensorFlow, SQL, and modern LLM tooling (Hugging Face, LangChain, OpenAI APIs).Skilled with entity extraction, topic modelling, network/graph analysis, and data sourcing or weak supervision in multilingual environments.Passion for climate, water, or environmental risk, and comfortable working in an early-stage, collaborative, low-ego environment.Nice to HavePhD / Postdoc with track record of pace and quality of publicationsGraph ML experience or multi-modal fusion (text geospatial).LLM fine-tuning for domain-specific tasks.Deployment experience with FastAPI, Docker, or similar frameworks.Background or exposure to environmental science, hydrology, or social-data analysis.
Benjamin ReavillBenjamin Reavill