Deep Learning & Computer Vision Research Engineer
Pubblicato il 04-08-2026 - European Tech Recruit in Bressanone
ph3Deep Learning Computer Vision Research Engineer /h3 /brpEuropean Tech Recruit are working closely with a computer vision deep learning research center, based in Bressanone, who are looking for an talented bDeep Learning Computer Vision Research Engineer /bto join their team.
/p /brpTheir 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.
/p /brh3Responsibilities as bDeep Learning Computer Vision Research Engineer /b: /h3 /brul /brliEvaluate state-of-the-art research in computer vision, deep learning, multimodal AI and generative models.
/li /brliTranslate industrial needs into research questions, datasets, benchmarks and proof-of-concept systems.
/li /brliDesign and validate models for anomaly detection, segmentation, classification, object detection, visual retrieval and measurement.
/li /brliAdapt foundation and vision-language models to specialised industrial domains and limited-data scenarios.
/li /brliDevelop data-efficient workflows using synthetic data, self-supervised learning, active learning and assisted annotation.
/li /brliBuild reproducible pipelines covering data acquisition, training, validation, deployment and model monitoring.
/li /brliDeliver maintainable software, technical documentation and demonstrators,
supporting technology transfer to industrial partners.
/li /br /ul /brh3Requirements: /h3 /brul /brliMSc with at least three years of relevant experience, or a PhD in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Engineering or a related field.
/li /brliProfessional proficiency in written and spoken English.
Italian and/or German are advantageous /li /brliStrong knowledge of modern computer vision and deep learning, including CNNs, Vision Transformers and foundation models.
/li /brliAbility to analyse research papers, reproduce results and translate new methods into working implementations.
/li /brliStrong Python and PyTorch skills, with familiarity with tools such as OpenCV, Open3D, PyTorch Lightning or Hugging Face.
/li /brliExperience in areas such as anomaly detection, segmentation, generative vision, multimodal learning, image retrieval or 3D vision.
/li /brliA data-centric approach to dataset collection, cleaning, annotation, versioning and quality assessment.
/li /brliUnderstanding of experimental design, benchmarking, reproducibility, model robustness and domain shift.
/li /brliExperience with GPU training, Linux, Git and containers; C++, MLOps, edge deployment and scientific publications are advantages.
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