SENIOR FULL STACK ENGINEER

About Symbiose

is a venture-backed deeptech company at the crossroads of

space-tech

and

nature-tech , pioneering the use of

AI , remote sensing, and High-Performance Computing (HPC) to transform how forests are monitored, managed, and valued. By fusing diverse

Earth Observation data , from hyperspectral, LiDAR, radar, and optical imagery, Symbiose delivers precise, real-time insights into forest health, carbon dynamics, and climate resilience. Our AI-driven platform empowers forest owners, investors, and insurers with actionable intelligence to accelerate FSC certification, enhance transparency, and drive a nature-positive economy.

Our Mission Is Simple But Ambitious : Make forest data actionable to protect biodiversity, enhance carbon capture, and make sustainable forestry the new norm.

Why join us? At Symbiose, you’ll join a passionate team working at the intersection of

AI

for good and climate innovation. You’ll have the freedom to experiment, the space to grow, and a direct impact on how forests are managed globally. Purpose-driven mission: your work contributes directly to forest conservation and climate resilience. Deep tech + impact: applied AI, geospatial analytics, and environmental modeling. Collaborative culture: open-minded, curious, and committed to real-world change. Based at Station F: Europe’s largest startup campus, surrounded by top innovators.

What we’re looking for : We’re always on the lookout for bold thinkers and builders, people who thrive at the frontier of technology and ecology. Whether your background is in machine learning, remote sensing, data engineering, forestry, or business development, if you care about the planet and cutting-edge innovation, you’ll fit right in.

Job Description Role Overview We are looking for a Senior Full Stack Engineer to design and scale the Symbiose Platform, our customer-facing application that brings deep environmental intelligence to users. You will work at the crossroads of backend, frontend, and data infrastructure, collaborating with remote sensing, geospatial, and machine learning engineers to integrate, deploy, and scale advanced EO algorithms into production. You’ll join a multidisciplinary team of engineers, scientists, and ecologists — where curiosity, autonomy, and impact drive every project. Together, we transform cutting‑edge research into real‑world, user‑ready solutions.

Key Responsibilities

Collaborate with Remote Sensing, Geospatial, and ML Engineers to integrate their algorithms into scalable APIs and data pipelines.

Design, implement, and operate large-scale imagery and data pipelines on Kubernetes.

Develop shared internal libraries to streamline the creation and maintenance of ETL workflows.

Manage multi‑cloud deployments (AWS / GCP / Azure) ensuring scalability, cost‑efficiency, and robustness.

Conduct solution trade‑offs on architecture, performance, and maintainability.

Work on challenging backend and pipeline projects supporting Symbiose’s multi‑cloud architecture.

Build and maintain Symbiose’s web interface using React and TypeScript, ensuring a performant, responsive, and intuitive experience.

Integrate Mapbox GL or equivalent libraries for geospatial data visualization.

Collaborate with product designers to translate mockups and wireframes into functional web experiences.

Participate in QA testing and agile delivery cycles, ensuring product quality and consistency.

Qualifications

5+ years of professional experience in software or data engineering.

Deep knowledge of React and TypeScript, including advanced typing concepts.

Experience designing scalable architectures in Kubernetes and Docker environments.

Strong command of PostgreSQL and schema design.

Experience with workflow orchestration tools (Airflow, Argo, etc.).

Familiarity with cloud services (AWS S3, SQS, Lambdas).

Excellent communication skills in English and comfort working in cross‑functional teams.

Nice to Have

Experience with geospatial and imagery pipelines.

Familiarity with geospatial data (geotiff, MBtiles, PMtiles,..)

Understanding of modern data formats (GeoParquet, COG).

Experience in data visualization, geospatial rendering, or climate tech.

Background in cloud architecture (resilience, error management).

Proficiency in Python (pytest, numpy, typing) and modern web frameworks.

Recruitment Process

Step 1: 30‑minute screening call with our People team

Step 2: Take‑home case study

Step 3: Feedback & culture‑fit interview

Step 4: Onboarding at Station F

We’re a fast-moving startup — the whole process takes

no more than two weeks .

Additional Information

Contract Type: Full‑Time

Location: Paris

Possible partial remote

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