Deep Learning & Computer Vision Research Engineer

Deep Learning & Computer Vision Research Engineer

European Tech Recruit are working closely with a computer vision & deep learning research center, based in Bressanone, who are looking for an talented Deep Learning & Computer Vision Research Engineer to join their team.

Their tech focuses on Industrial Multimodal AI: systems that combine images, video, 3D data, machine and sensor data, natural language, foundation models and generative AI to solve complex production and inspection challenges.

Responsibilities as Deep Learning & Computer Vision Research Engineer :

• Evaluate state-of-the-art research in computer vision, deep learning, multimodal AI and generative models.
• Translate industrial needs into research questions, datasets, benchmarks and proof-of-concept systems.
• Design and validate models for anomaly detection, segmentation, classification, object detection, visual retrieval and measurement.
• Adapt foundation and vision-language models to specialised industrial domains and limited-data scenarios.
• Develop data-efficient workflows using synthetic data, self-supervised learning, active learning and assisted annotation.
• Build reproducible pipelines covering data acquisition, training, validation, deployment and model monitoring.
• Deliver maintainable software, technical documentation and demonstrators, supporting technology transfer to industrial partners.

Requirements:

• MSc with at least three years of relevant experience, or a PhD in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Engineering or a related field.
• Professional proficiency in written and spoken English. Italian and/or German are advantageous
• Strong knowledge of modern computer vision and deep learning, including CNNs, Vision Transformers and foundation models.
• Ability to analyse research papers, reproduce results and translate new methods into working implementations.
• Strong Python and PyTorch skills, with familiarity with tools such as OpenCV, Open3D, PyTorch Lightning or Hugging Face.
• Experience in areas such as anomaly detection, segmentation, generative vision, multimodal learning, image retrieval or 3D vision.
• A data-centric approach to dataset collection, cleaning, annotation, versioning and quality assessment.
• Understanding of experimental design, benchmarking, reproducibility, model robustness and domain shift.
• Experience with GPU training, Linux, Git and containers; C++, MLOps, edge deployment and scientific publications are advantages.

If this role is of any interest please apply directly on LinkedIn or send a copy of your CV to [email protected].

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