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AI Tech Lead at SITA
I am a determined and innovative Machine Learning Engineer with over six years of experience in developing and implementing AI solutions. My expertise lies in Deep Learning, with a special focus on Computer Vision. Currently, I am working at Midokura, a part of the Sony Group, where I have been instrumental in delivering AI solutions that meet complex requirements under significant constraints. Throughout my career, I have participated in multi-disciplinary teams and contributed to the successful completion of various AI projects. I have a strong foundation in AI frameworks such as Tensorflow, Pytorch, and ONNX, and I am proficient in programming languages including Python, C++, and Matlab. While I have some experience with cloud platforms like AWS, SageMaker, and Azure, I am keen to further develop these skills to ensure scalable and efficient deployment of AI models. I am passionate about continuous learning and thrive on applying my skills to tackle new and challenging problems. I am eager to contribute to innovative projects and collaborate with dynamic teams to drive technological advancements in the field of AI and Machine Learning. Outside of work, I enjoy trekking, diving, and practicing Taekwondo. I am an avid reader and find great joy in roleplaying games, which fuel my imagination and collaborative spirit.
Universitat Politècnica de Catalunya
Master Degree in Artificial Intelligence, Computer Science
January 1, 2015 – January 1, 2017
Universitat Politècnica de Catalunya
Bachelor of Computing in Computer Science, Artificial Intelligence
January 1, 2011 – January 1, 2015
SITA
AI Tech Lead
August 1, 2025 – Present
Barcelona, Catalonia, Spain · Hybrid
Midokura
Artificial Intelligence Researcher
February 1, 2020 – June 1, 2025
Barcelona, Catalonia, Spain · Hybrid
GoldenSpear, LLC
Artificial Intelligence Researcher
February 1, 2017 – February 1, 2020
GoldenSpear, LLC
Artificial Intelligence Intern
June 1, 2016 – January 1, 2017
Universitat Oberta de Catalunya (UOC)
Researcher Assistant
October 1, 2014 – June 1, 2016
Greater Barcelona Metropolitan Area
Master Thesis - "Face recognition using Deep Learning"
June 1, 2016 – January 1, 2017
As part of this master thesis, I developed a fully functional Face Recognition system based on Convolutional Neural Networks. Given a picture in an uncontrolled environment, this system was able of detecting and recognizing people from hundreds of available identities. I developed it in the span of 6 months as a project for GoldenSpear, and it achieved higher than 95% accuracy on benchmarking datasets.
Bachelor Thesis - "Implementation and study of a deep and wide Kernel Machine"
January 1, 2015 – June 1, 2015
This project consisted in the implementation and testing of a type of Deep Kernel Machine, in particular the arc-cosine kernel. In this project, these predictions consisted in correctly classifying handwritten digits using the MNIST dataset. This project was implemented in C++.
Deep Learning Specialization
Coursera Course Certificates
June 24, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera Course Certificates
June 24, 2026 – Present
Certificate of Proficiency in English - Grade B
Cambridge English
June 24, 2026 – Present
Convolutional Neural Networks
Coursera Course Certificates
June 24, 2026 – Present
Structuring Machine Learning Projects
Coursera Course Certificates
June 24, 2026 – Present
Neural Networks and Deep Learning
Coursera Course Certificates
June 24, 2026 – Present
Sequence Models
Coursera Course Certificates
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a consistent career path focused on AI/ML research and development, aligning well with a specialized ML Engineer role. Experience spans academic research, AI internships, and full-time researcher/tech lead roles in AI-centric companies. The project diversity is somewhat limited to Computer Vision, but the depth in this area is significant. The transition to an 'AI Tech Lead' role indicates growth and leadership potential. However, the lack of diverse project types beyond computer vision might limit broader cultural fit for roles requiring a wider ML application spectrum.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight collaboration with international teams, leading multidisciplinary research teams, and creating detailed business plans, suggesting strong soft skills in teamwork, leadership, and project management. The role as 'AI Tech Lead' further supports leadership potential. Operational fit is good given the focus on developing and deploying AI solutions.