Beschreibung
Job Title: Freelance Computer Vision Specialist – Industrial Automation
Location: Remote (Client based in Germany)
Contract Type: Freelance
Duration: 6 months (extension possible)
Language: English (German a plus)
About the Role
We are supporting a German industrial automation client seeking a freelance Computer Vision Specialist to improve the accuracy and efficiency of real-time visual inspection systems in their production line. The ideal candidate will have deep experience in classical and modern computer vision techniques, with a track record of deploying vision models in live manufacturing or robotics environments.
Responsibilities
- Develop and refine computer vision models for object detection, classification, and segmentation using factory camera data
- Implement and optimize pipelines for real-time image processing and video analytics
- Work with domain experts and systems engineers to integrate CV models into existing automation systems
- Perform dataset curation, labeling, augmentation, and continuous model improvement
- Apply deep learning and classical vision techniques depending on task complexity and latency constraints
- Validate model performance in edge environments or constrained hardware
- Document processes and support handover to the internal engineering team
Requirements
- 5+ years of experience in computer vision or deep learning engineering
- Expert in Python and libraries such as OpenCV, NumPy, and Scikit-image
- Strong knowledge of deep learning frameworks (e.g. TensorFlow, PyTorch)
- Experience with object detection models (e.g. YOLOv5/v8, Faster R-CNN, Mask R-CNN, SSD)
- Hands-on experience working with industrial camera systems or robotic vision pipelines
- Knowledge of edge deployment (e.g. NVIDIA Jetson, TensorRT, ONNX, OpenVINO) is highly desirable
- Comfortable working with image annotation tools and data labeling workflows
- Familiar with real-time inference optimization and model quantization techniques
- Excellent problem-solving skills and ability to collaborate across teams
Preferred Tech Stack
- Languages & Libraries: Python, OpenCV, Pillow, NumPy, PyTorch, TensorFlow, Scikit-image
- Models & Frameworks: YOLOv5/v8, Detectron2, Faster R-CNN, ONNX
- Tooling: Label Studio, Roboflow, ClearML, MLflow
- Hardware/Deployment: NVIDIA Jetson, TensorRT, Docker, OpenVINO
- Cloud & DevOps: AWS/GCP/Azure, CI/CD, Git, Docker
- Visualization: Matplotlib, Streamlit, Dash
Location: Remote (Client based in Germany)
Contract Type: Freelance
Duration: 6 months (extension possible)
Language: English (German a plus)
About the Role
We are supporting a German industrial automation client seeking a freelance Computer Vision Specialist to improve the accuracy and efficiency of real-time visual inspection systems in their production line. The ideal candidate will have deep experience in classical and modern computer vision techniques, with a track record of deploying vision models in live manufacturing or robotics environments.
Responsibilities
- Develop and refine computer vision models for object detection, classification, and segmentation using factory camera data
- Implement and optimize pipelines for real-time image processing and video analytics
- Work with domain experts and systems engineers to integrate CV models into existing automation systems
- Perform dataset curation, labeling, augmentation, and continuous model improvement
- Apply deep learning and classical vision techniques depending on task complexity and latency constraints
- Validate model performance in edge environments or constrained hardware
- Document processes and support handover to the internal engineering team
Requirements
- 5+ years of experience in computer vision or deep learning engineering
- Expert in Python and libraries such as OpenCV, NumPy, and Scikit-image
- Strong knowledge of deep learning frameworks (e.g. TensorFlow, PyTorch)
- Experience with object detection models (e.g. YOLOv5/v8, Faster R-CNN, Mask R-CNN, SSD)
- Hands-on experience working with industrial camera systems or robotic vision pipelines
- Knowledge of edge deployment (e.g. NVIDIA Jetson, TensorRT, ONNX, OpenVINO) is highly desirable
- Comfortable working with image annotation tools and data labeling workflows
- Familiar with real-time inference optimization and model quantization techniques
- Excellent problem-solving skills and ability to collaborate across teams
Preferred Tech Stack
- Languages & Libraries: Python, OpenCV, Pillow, NumPy, PyTorch, TensorFlow, Scikit-image
- Models & Frameworks: YOLOv5/v8, Detectron2, Faster R-CNN, ONNX
- Tooling: Label Studio, Roboflow, ClearML, MLflow
- Hardware/Deployment: NVIDIA Jetson, TensorRT, Docker, OpenVINO
- Cloud & DevOps: AWS/GCP/Azure, CI/CD, Git, Docker
- Visualization: Matplotlib, Streamlit, Dash