Nuestro cliente: líder internacional en el diseño de sistemas de análisis de vídeo basados en tecnologías de inteligencia artificial y visión por computador. Desarrollan algoritmos patentados altamente sofisticados para proteger y garantizar la seguridad de empresas, propiedades e infraestructuras críticas. Presente en más de 40 países y con 40.000 canales de video vendidos en todo el mundo; estando a la vanguardia del análisis de vídeo desde 2005.
We are looking for Computer Vision & AI Engineer to join their growing R&D team in Bellaterra. Engineers who want to push the boundaries of applied AI, working hands‑on with real products and real customers, and making a tangible impact.
You will work on advanced video analytics solutions for safety- and mission‑critical environments, tackling open‑ended, real‑world problems. You will be involved in the full lifecycle of video understanding challenges — from defining the AI approach, to training, evaluating, and deploying models that operate reliably on multi‑camera video streams.
Requirements

Master’s or PhD in Computer Vision, Artificial Intelligence, Machine Learning, or a related field.
+2 yeras of professional experience in Computer Vision and/or Deep Learning, applied to real‑world Artificial Intelligence systems.
Hands‑on experience with Python, PyTorch, C++
Strong analytical, communication, and problem‑solving skills.
Experience with image and/or video analysis systems in production or near‑production environments is a PLus
Hands‑on experience with OpenVINO or TensorRT (pluses).

Ofrecen

Un salario competitivo: 35-45k€ brutos/año a negociar en función de experiencia contrastada.
Un ambiente de trabajo dinámico y de colaboración.
Oportunidad de carrera desafiante y gratificante.
Plan de formación y desarrollo profesional en una empresa líder en inteligencia artificial.
Trabajo presencial a tiempo completo con horarios de trabajo flexibles.
Días disponibles para trabajar desde casa (15 días/año).
Contrato indefinido.

What You Will Do

Work with state‑of‑the‑art architectures, including transformers and vision‑language models, to tackle new challenges.
Design, train, and evaluate deep learning models for image and video analysis.
Improve and extend our AI capabilities to new object types, behaviors, and application domains.
Integrate trained models into edge‑deployed production pipelines.

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