ML Engineer (Computer Vision)
Andersen is hiring an ML Engineer (Computer Vision) for a project developing an image analysis platform to automate defect detection and improve quality control in electroplating and surface finishing. Our customer is an international company providing specialized industrial materials and technology solutions to businesses across multiple sectors. Combining technical expertise with research and development capabilities, the organization helps customers improve manufacturing processes, enhance product quality, and increase operational efficiency. Its activities focus on delivering innovative solutions, supporting sustainable industrial practices, and adapting to evolving technological and market requirements. The project is focused on developing and enhancing an image analysis platform for quality control in electroplating and surface finishing processes. It leverages Machine Learning and Computer Vision to automate defect detection, image segmentation, feature measurement, and comparison with expert reference values, enabling accurate, consistent, and objective quality assessments.
Responsibilities
- Developing and optimizing Computer Vision models for automated analysis of test panel images.
- Building semantic segmentation and image classification models (binary and multi-class).
- Implementing image-based feature extraction, including size and position of visual characteristics.
- Optimizing existing models and scaling the approach to a larger number of sample types.
- Preparing and optimizing datasets, working with labeled data and ground truth provided by experts.
- Validating model results against expert reference assessments and reporting quality metrics.
- Integrating models into the AWS-based pipeline together with Cloud / MLOps and Data Engineering.
- Documenting models, experiments and validation results for knowledge transfer.
Requirements
- Experience in Machine Learning/Data Science for 5+ years, including 3+ years of hands-on Computer Vision experience on real projects.
- Strong experience with semantic segmentation in applied or production environments.
- Experience with image classification and feature extraction, including object size, position, and measurements.
- Hands-on experience with the full ML model lifecycle, including training, fine-tuning, and validation using PyTorch or TensorFlow.
- Experience working with ground-truth datasets and evaluating models against expert annotations.
- Strong proficiency in Python and OpenCV.
- Experience optimizing existing models and scaling solutions to support multiple classes.
- Level of English – from Intermediate+ and above.
Nice to have
- Experience with industrial visual inspection, defect detection, surface/microscopy image analysis, or medical imaging.
- Experience with AWS (S3, SageMaker) and Docker.
- Knowledge of inference optimization using ONNX or similar technologies.
- Experience with data labeling tools and annotation quality control.
- Ability to read C++ code, particularly OpenCV-based annotation tools.
Compensation: 3050–5000 EUR per month.
