Job description
Cyclops is an AI-powered platform for measuring, monitoring, and verifying natural capital at scale. Our mission is to turn petabytes of Earth observation imagery into auditable metrics of carbon stocks, vegetation health, and land use change so that climate finance can flow where it matters. We’re looking for a hands-on engineer who can cultivate the full stack from the API to the frontend and everything in between.
Why this role is unique
Own the product & the pipeline: You’ll design everything from ingestion of raw Sentinel/Landsat scenes to the API that powers on-chain carbon registries and dashboards.
Impact at scale: Each line of code helps move millions of tonnes of CO₂ equivalent through verifiable nature-based projects.
Novel technology: No legacy cruft. Pick the right datastores, cloud primitives, and CI/CD flows from day one.
Educational environment: You will work with professors and academics who are top of their fields so you understand the why, while doing the how.
Path to leadership: You’ll play a role in hiring and mentoring subsequent engineers, setting technical direction for years to come.
What you’ll be doing
Architect end-to-end systems
- Design satellite-image processing pipelines (GEE → xarray → Parquet/Zarr/IPFS) and the microservices that expose results via GraphQL/REST.
Ship product features
- Build dashboards in Next.js/React and geospatial APIs in Node/Python/FastAPI that climate-finance customers love.
Scale & harden
- Automate everything with IaC (Terraform/Pulumi), CI/CD, and robust monitoring. Profile memory & I/O to keep petabyte workflows affordable.
Prototype & iterate
- Turn vague carbon-methodology specs into data models, algorithms, and user-facing tools.
Lead & mentor
- Establish engineering best practices, run code reviews, and recruit the next generation of Cyclops engineers.
You might be a fit if you have
Fluency across the stack: Typescript, React/Next.js, Node.js and Python for data/ML work.
Data-infrastructure chops: Dask/DuckDB; S3 & object-store patterns; Data pipelining with Apache Airflow, columnar formats (Parquet, Arrow) and chunked stores (Zarr, Cloud-Optimized GeoTIFF).
GIS / remote-sensing know-how: Google Earth Engine, QGIS, Rasterio, GDAL, PROJ, xarray, GeoPandas, STAC, EO tiling schemes, basic radiometric corrections.
Data Visualization skills: D3/Charts.js, Mapbox/Leaflet
Cloud & DevOps skills: Bare Metal/Linux, Docker, IaC, observability (Prometheus/Grafana, OpenTelemetry).
Systems thinking: Comfortable reasoning about distributed systems, eventual consistency, and data-versioning at petabyte-plus scale.
Bias for action & ambiguity tolerance: You turn half-written Notion docs into shipped features without hand-holding.
Mission-driven: You want your work to fight climate change.
Extra credit
Experience leading a small team or owning a large production system.
Familiarity with IPFS/IPLD, content addressable storage, or on-chain data proofs.
Solidity / Foundry / Hardhat exposure (we bridge geospatial data to smart contracts).
GPU accelerated image processing (cuDF, RAPIDS, TorchGeo).
Machine Learning knowledge and MLOps (PyTorch/TensorFlow)
Experience with carbon/MRV methodologies or environmental science.
What we offer
Competitive salary + meaningful equity
Remote-first, async-friendly culture with team members and hubs in Europe and USA
Stipend for hardware, conferences, and learning.
The chance to write the playbook for geospatial data in decentralized climate finance.
How to apply
Email [email protected] with:
“Cyclops Forest Wizard” in the subject line.
Your resume and GitHub / portfolio links.
A short note (<300 words) describing the most complex data pipeline you’ve built and what you’d do differently next time.
We review every application personally. If you’re excited by satellites, big data, and real-world impact, let’s talk.
