Scope: Deployment engineer to design, implement, evaluate and deploy production‑ready CV/Deep Learning solutions for industrial applications (visual inspection, recognition, segmentation, tracking, video analytics) Salary range : €50,000 – €70,000 gross/year (depending on experience) Location: Turin Stack: Python, scikit‑learn, PyTorch, CI/CD, Azure/AWS, Edge/On‑prem constraints, GPU/CUDA real‑time inference, VLM Role Summary Within the Deployment Unit, we are looking for a Computer Vision and AI Engineer to develop production‑ready AI solutions for industrial applications. This is a hands‑on role for someone with strong coding skills , solid experience in Deep Learning and Computer Vision , and the ability to translate complex visual AI problems into reliable, scalable systems . The role focuses on areas such as visual recognition, quality inspection, segmentation, and video analytics . The candidate will work across the full lifecycle : experimental design, model implementation, training, evaluation, optimization, deployment, and production support. You will work closely with: Deployment and Data Science team , delivering production‑grade ML systems Research units , to industrialize promising use cases emerging from applied research Industrial partners , ensuring solutions meet real operational needs and performance targets What You Will Do Scope projects and their technical feasibility through client interaction Design and develop computer vision and deep learning solutions for industrial applications such as anomaly detection, object recognition, segmentation, tracking, and large‑scale video analytics. Build robust AI pipelines for data preprocessing, annotation, model training, validation, inference, and monitoring. Evaluate model performance using appropriate technical and business metrics, considering accuracy, latency, robustness, scalability, and deployment feasibility. Develop high‑quality software by leveraging AI tools and using sound engineering practices, including Git, testing, debugging, containerization, CI/CD, and deployment automation. About You Master’s degree in Computer Science, Engineering, Physics or related; PhD a plus. Strong proficiency in Python and deep Learning (e.g., PyTorch ). Hands‑on experience with at least part of the following areas: object detection, image segmentation, object tracking, image/video classification, anomaly detection, or visual inspection applied to industries, logistics or robotics. Use agentic AI‑assisted coding workflows (e.g., Claude Code, Codex) daily to speed up development and fill knowledge gaps. Experience working with large‑scale image and/or video datasets and designing reproducible experimental setups. Strong software engineering mindset and ability to support the full lifecycle from prototype to production deployment. Experience with vision‑language models (VLM), synthetic data or multi‑stage model (detection, segmentation, 3D pose estimation) for robotics. Expertise in one or more of the following cloud providers : Google Cloud Platform, AWS, Azure. Proficiency in English . Nice to Have Experience deploying and optimizing real‑time inference on GPU/CUDA , edge devices or cloud platforms. Experience with industrial AI , quality control, logistics, robotics. Proficiency in Italian . What We Offer Access to our advanced computing infrastructure A team with engineers and researchers working together on real industrial AI deployments Chance to co‑author papers for top‑tier conferences like NeurIPS, ICML, CoRL, and RSS Exposure and collaboration with a huge network of corporates, SMEs, startups and technology partners An exceptional workplace at OGR, Turin at the epicenter of tech Lots of learning opportunities : IAS, internal Academy, budget for events, conferences and online courses Relocation incentives and competitive benefits package (including potential tax advantages for international candidates, where applicable) #J-18808-Ljbffr
Computer Vision And Ai Engineer
THE ITALIAN INSTITUTE OF ARTIFICIAL INTELLIGENCE (AI4I)
torino, torino
Pubblicato 13 giorni fa
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