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# Computer Vision Engineer | Berlin, Hybrid

- **Company:** Airteam Aerial Intelligence GmbH
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Computer Vision, Software as a Service, Data Transformation, Github, Python (Programming Language), Machine Learning, Object Detection, Software Engineering, Cloud Platform System, Pytorch, Deep Learning, Kubernetes, Machine Learning Operations, Docker
- **Published:** October 2, 2026
- **Apply:** https://www.adzuna.de/details/5905861368

## About the Role

* 2-4 years of commercial experience in data science/ML, including Computer Vision and Deep Learning
 * Experience across the full ML lifecycle (preprocessing, training, evaluation, deployment, monitoring), incl. conda and MLflow or comparable tools
 * Solid software engineering skills: Python, Git/GitHub, Docker/Kubernetes, cloud platforms
 * Strong problem-solving, communication and teamwork skills, plus a willingness to learn new tools quickly

**
Nice-to-have**

 * Experience in construction or a related industry
 * Experience with our stack: GCP, Vertex AI, PyTorch, Conda, MLflow, GitHub, Argo Workflows
 * Experience building and maintaining ML pipelines
 * A goal-oriented, "just do it" mentality

## Description

Airteam is a Berlin-based SaaS startup with an AI-powered cloud platform for roofers and solar planners. As a mid-level Computer Vision Engineer, you'll build 2D-to-3D object detection and automatic geometry reconstruction from drone data. Your work helps roofers and solar planners make informed decisions and drives a climate-neutral product.

Tasks

 * Develop and implement computer vision algorithms for 2D-to-3D object detection using drone data
 * Integrate ML models into our platform together with the engineering teams
 * Build end-to-end ML pipelines with GCP, Python, Argo, PyTorch and MLflow
 * Implement data preprocessing, model training, deployment and monitoring
 * Visualize and communicate findings to stakeholders


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