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What is a Computer Vision Engineer?
Complete job profile for your hiring: role and responsibilities, required skills, training, salary, and career progression
The Computer Vision Engineer develops algorithms that can analyze and understand images or video.
They work on a wide variety of use cases: facial recognition, medical imaging, security, automotive, retail, Industry 4.0, and more.
Why is the Computer Vision Engineer role strategic?
The explosion of visual data and deep learning models has created a strong need: interpreting images automatically.
The Computer Vision Engineer turns these visual streams into automated decisions or actionable data.
Their responsibilities
- Develop and train vision models (CNNs, transformers, diffusion models…).
- Annotate and preprocess visual datasets.
- Evaluate model performance and robustness.
- Work on putting models into production (MLOps / Edge AI).
- Collaborate with R&D, product, and hardware teams (cameras, sensors).
Team collaboration
They often work with:
- Data Scientists for the algorithmic side.
- Embedded Engineers for deployment.
- AI Product Managers for concrete use cases.
Key skills of the Computer Vision Engineer
Technical:
- Python, OpenCV, PyTorch, TensorFlow
- YOLO, Detectron2, Segment Anything
- MLOps, model/inference optimization
- Hardware and edge computing fundamentals
Soft skills:
Creativity, scientific rigor, attention to detail and performance.
Training & salary
- Master's or PhD in computer science, signal processing, vision, or AI.
- Average salary: €45K–€60K (junior), €70K–€90K (confirmed), up to €120K+ (senior, R&D).
Possible career progression
Lead Computer Vision Engineer, Research Scientist, or Head of AI.