Full Stack Developer: Geospatial & ML Systems

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., * 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.

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.

• 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.