JOB DESCRIPTION

 

The successful candidate will join the Germans Trias i Pujol Research Institute (IGTP) as part of a multidisciplinary team developing AI-based computer vision systems for surgical instrument recognition, at the intersection of artificial intelligence, computer vision and clinical practice. The project is carried out in collaboration with HealthTech Innovations and is deployed on a robotic platform used in the central sterilization unit and operating rooms of the Hospital Universitari Germans Trias i Pujol.
The role is centered on the design, training and optimization of computer vision and deep learning algorithms — covering the full pipeline from data acquisition and labeling to model training, evaluation and deployment. The robotic platform on which these algorithms run is developed and maintained by the project's robotics engineering team; prior professional experience in industrial robotics is not required, although a basic understanding of how perception systems interact with robotic control loops is expected and can be consolidated on the job.

This position requires a high level of technical autonomy: writing, testing and maintaining production-level code, training and iterating on models, and contributing to architectural decisions for the AI system. Candidates able to take ownership of the technical roadmap independently — whether coming from a senior background or from a strong junior profile with some hands-on experience — are especially encouraged to apply.

The position is part of a strategic research and innovation project with strong clinical impact, aimed at advancing the state of the art in computer vision for medical devices and supporting the digital transformation of surgical workflows.

MAIN RESPONSIBILITIES

• The selected candidate will play the lead technical role in the development of the AI-based surgical instrument recognition system, with direct responsibility for the design, training and performance of its computer vision and machine learning components.
• Main responsibilities include the design and development of computer vision pipelines for surgical instrument detection, classification and tracking, covering the full lifecycle from data acquisition and preprocessing to model training, evaluation and deployment. The candidate will write, optimize and maintain production-quality code, ensuring robustness, scalability and reproducibility of the AI models.
• The role involves training and fine-tuning machine learning and deep learning models, selecting appropriate architectures, defining evaluation metrics and implementing strategies to improve accuracy and generalization in real hospital environments. The candidate will lead the generation of datasets, including defining labeling strategies and data augmentation techniques, and will iterate on models based on validation results.
• Working in coordination with the robotics engineering team at HealthTech Innovations, the candidate will support the integration of the AI/computer vision modules into the robotic platform, focusing on the perception side of the perception–action loop. Deep involvement in the mechanical or control engineering of the robotic platform itself is not expected.
• The candidate will also be involved in testing and validating the system in the central sterilization unit and operating room, analyzing performance, identifying limitations and proposing technical improvements.
• Documentation of algorithms, code and experimental results will be part of the role, supporting regulatory processes and scientific dissemination.
• Overall, this position entails a high level of technical responsibility and autonomy, with a strong focus on applied AI and computer vision, and a direct impact on the development of a novel medical device for surgical environments.

QUALIFICATIONS AND EXPERIENCIE

• Degree in Computer Science, Telecommunications Engineering, Data Science, Artificial Intelligence, Mathematics/Physics with a computational focus, or a related technical field.
• A Master’s degree or specialized training in Artificial Intelligence, Machine Learning, Deep Learning or Computer Vision; or equivalent professional experience in the development and application of these technologies.
• Candidates with a background in Robotics Engineering or Automation are equally welcome, provided they can demonstrate strong, hands-on AI/computer-vision experience.
• Proven, hands-on experience developing computer vision and deep learning systems for real-world applications: object detection, segmentation, classification and/or tracking.
• Proficiency in Python, together with practical experience in at least one major deep learning framework (PyTorch or TensorFlow).
• Experience with OpenCV.
• Experience with the full model lifecycle — dataset generation, labeling strategy, data augmentation, training, evaluation and iterative optimization — is expected, ideally in applied or industrial contexts rather than purely academic settings.
• Knowledge of surgical instruments or medical environments will be considered an asset, although strong motivation and the ability to quickly adapt to a hospital setting are equally important. The role involves working closely with clinical staff, so the candidate must be comfortable operating in multidisciplinary environments.
• Fluency in Spanish, given the need to coordinate directly and fluidly with clinical staff; Catalan is valued as an asset. A good level of English is also expected, for technical documentation, scientific communication and collaboration with academic partners.
• The candidate should demonstrate strong problem-solving skills, autonomy and a proactive attitude, together with genuine ownership of technical decisions — this is a role for someone who wants to drive the AI/computer vision development of the project, not simply execute predefined tasks.
• Availability to commute regularly to the Hospital Universitari Germans Trias i Pujol or to the HealthTech Innovations S.L. offices, the technical partner in the consortia, in Premià de Mar is mandatory.

Valuable:

• Knowledge of C/C++ and of robotics middleware (e.g. ROS).
• Prior exposure to robotic perception systems or to the integration of AI components into a robotic platform (training on the specific platform will be provided).

WHAT WE OFFER

• Indefinite contract by science law linked to the project: Project CPP2024-011704 is funded by MICIU/AEI/10.13039/501100011033/ FEDER, EU (100% dedication to the project by the hired person). (Contrato indefinido por actividades científico-técnicas)
• We offer an immediate incorporation into a highly innovative applied research and development project at the intersection of artificial intelligence, robotics and healthcare, with direct impact on real clinical environments.
• The position is full-time, with a 39-hour work week, offering a flexible working schedule. 
• The role allows for partial remote work, while requiring regular on-site collaboration sessions at the offices of HealthTech Innovations in Pineda de Mar, as well as presence at the Hospital Universitari Germans Trias i Pujol when project activities require it. This hybrid model ensures both technical focus and close coordination with the development and clinical teams.
• The position includes 23 days of paid annual leave, plus 5 additional days for personal matters, + 2 days for Easter + 2 days for Christmas supporting a healthy work–life balance.

FOR MORE INFORMATION

https://www.germanstrias.org/ca/

RESOLUCION

HOW TO APPLY

Interested persons must attach to the application:

• Motivation letter explaining their interest in the position.
• Updated CV.
• Contact of 2-3 references.

Applications will be evaluated in accordance with the guiding principles and objectives of the supply systems, following the process described below:

Curricular evaluation: analysis of the curriculum vitae to assess aspects related to training, professional career and experience in positions related to the job position under selection.

Personal interview: once the résumé has been evaluated, the selected candidates will be called for a personal interview to verify and expand on the information detailed in the résumé and to evaluate aspects related to experience and professional skills.

Applications that do not meet the requirements, that are not included in the cases foreseen or that are not processed in accordance with the established procedure will not be considered in the selection process.

DEADLINE FOR APPLICATIONS

The call for applications will close on July 22nd, 2026