Deep Learning
14 ore fa
brixen, trentino alto adige, Italia
European Tech Recruit
Tempo pieno
Gratuito con email o Google
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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
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