Core Tech: .NET, Python, React (Modern Frontend)
Focus: Bridging the gap between High-Resolution Data and Machine Learning
The Role
As a Full Stack Developer at Cyclomedia, you won’t be boxed into a single application. You will be working across our software ecosystem. Your mission is to build the internal platforms and user-facing tools that process, visualize, and label the world’s most accurate street-level data.
You will act as the technical glue between our .NET-based enterprise infrastructure and our Python-driven Machine Learning research, ensuring that high-performance data flows seamlessly from our 360-degree cameras to our AI models.
Tasks
Key Responsibilities
* System Architecture: Design and maintain scalable microservices using .NET and Python that handle massive geospatial datasets.
* Next-Gen UI/UX: Build highly responsive frontends (React/TypeScript) capable of rendering complex 2D and 3D data (imagery, LiDAR, and vector overlays).
* ML Enablement: Collaborate with the Machine Learning team to build "Human-in-the-Loop" systems, automation pipelines, and model monitoring dashboards.
* AI Integration: Leverage AI-powered development tools (IDEs, LLM-coding assistants, and automated testing) to maintain high code quality and speed.
* Data Orchestration: Manage the lifecycle of geospatial data, ensuring it is optimized for both human interaction and algorithmic processing.
Requirements
Technical Requirements
* Backend: Proficiency in C# / .NET (Core/8) for enterprise logic and Python (FastAPI/Django) for data processing and ML integration.
* Frontend: Strong experience with Modern React (Hooks, State Management) and TypeScript. Knowledge of WebGL or Three.js is a significant advantage.
* Cloud & DevOps: Familiarity with Docker, Kubernetes, and cloud-native development.
* The "AI-First" Mindset: You are an early adopter of AI IDEs (like Cursor or GitHub Copilot) and know how to use them to multiply your output.
* Problem Solver: A "Swiss Army Knife" mentality—able to pivot from low-level data optimization to high-level UI design.
Benefits
What We Offer
* Starting Salary: €70,000 per year, with a clear trajectory for increases based on your technical contributions and mastery.
* Diverse Projects: From internal automation tools to high-scale data platforms—your work will never be repetitive.
* Innovation-Driven Environment: Direct access to state-of-the-art ML workflows and a seat at the table in deciding our future tech stack.
Skills Required
- Proficiency in C# / .NET (Core/8) for enterprise logic
- Proficiency in Python for data processing and ML integration (FastAPI or Django)
- Strong experience with Modern React (Hooks, state management) and TypeScript
- Experience building scalable microservices handling large geospatial datasets
- Experience rendering and visualizing complex 2D/3D data (imagery, LiDAR)
- Familiarity with Docker, Kubernetes, and cloud-native development
- Knowledge of WebGL or Three.js
- AI-first mindset; early adopter of AI IDEs/LLM coding assistants (e.g., Cursor, GitHub Copilot)
- Ability to collaborate with ML teams on human-in-the-loop systems, automation pipelines, and model monitoring
- Versatile problem-solving ability across low-level data optimization and high-level UI design
What We Do
Founded in 1980 and based in the Netherlands CycloMedia is a leading international provider of data and software solutions virtualising the outside world accurately on-screen. CycloMedia’s customers derive actionable insights from the geo-data platform to power day-to-day decisions remotely and with more accuracy, delivering exceptional ROI. CycloMedia provides a rich end-to-end B2B geo-data and software platform and has an established presence in the US, Dutch, German and Scandinavian markets. Using proprietary cloud-based technologies, CycloMedia’s high accuracy data sets allow governments and enterprises to assess, analyze and measure physical infrastructures, including buildings, roads and other assets, remotely, and on any device. CycloMedia is uniquely global in its ability to deliver its customers actionable insights from geo-data rapidly and at scale.









