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Senior Research/Machine Learning Engineer @ Zattoo | Master's in AI
With over a decade of experience in the tech industry, I currently work as a Senior Research/Machine Learning Engineer, specializing in AI-driven personalization and deep neural networks. My focus is on deploying Recommender Systems using NLP, Learning to Rank, and Reinforcement Learning to enhance media personalization. I also fine-tune and deploy Large Language Models (LLMs) locally, ensuring optimal performance and security for business-specific use cases. My background includes research in Generative AI (BERT, GPT), SuperResolution techniques, and developing real-time Computer Vision systems, like ad detection in TV streams. Additionally, I implement intelligent chatbots and AI assistants, tailored to improve user engagement and streamline operations. Passionate about innovation, I’m committed to delivering impactful AI solutions that align with business goals.
Universidad Nacional de Educación a Distancia - U.N.E.D.
Master's degree in Advanced Artifitial Inteligence , Artifitial Inteligence
January 1, 2017 – January 1, 2020
Universidad Europea
Grado en Ingenieria Informática, Computer Software Engineering
January 1, 2009 – January 1, 2011
Universidad de La Laguna
Ing Técnica en Informática de Gestión, Developer
January 1, 2003 – January 1, 2009
Zattoo
Research/Machine Learning Engineer
November 1, 2017 – Present
Zattoo
iOS Software Engineer
March 1, 2014 – December 1, 2017
RapidShare AG
Mobile Developer
November 1, 2013 – March 1, 2014
Zürich Area, Switzerland
ODIGEO
iOS Developer
December 1, 2012 – November 1, 2013
Las Rozas de Madrid, Community of Madrid, Spain
Fidiliti
Senior iOS Developer
May 1, 2012 – December 1, 2012
Greater Madrid Metropolitan Area
3DS, 3 Days Startup
Emprendedor Participante con Idea y Negocio
May 1, 2012 – May 1, 2012
Greater Barcelona Metropolitan Area
beMee
Desarrollador de IOS
January 1, 2012 – May 1, 2012
Leganes
Gigigo
Becario
April 1, 2011 – January 1, 2012
C/ Dr. Zamenhof 36 bis, 1°A
Recommender System
September 1, 2017 – Present
We have developed an algorithm in order to provide recommendations for our users. We started with a model where we find the latent dynamics of our content and encode them into an embedding space. Afterwards, we use some Learning2Rank algorithm in order to optimize the usage per each user. We also have researched the use of a Multi-armed bandit approach for some element placement.
Applying Deep Geneative Models into the SuperResolution problem
September 1, 2017 – June 1, 2020
I tried several approaches of Generative Adversarial Networks, facing the typical problems these networks have as Mode Collapse and training instability. I saw this approach was learning a direct map 1:1 (LR->HR) rather than the conditional probability distribution, so I decided to switch into a more complex approach. Furthermore, I focused into learning a latent representation, using Stylegan, training the network with CelebA dataset. I modified the dataset, having the original version of each image in HR, plus the same image in LR. Stylegan was capable of learning the dynamics that encode the images and their relation besides the visual features also the quality features. So an image in LR, in some of the multiple dimensions we had in the latent space, is close to the several HR images that correspond to the same LR image. We are using the quality as a feature of the image. In order to learn the conditional probability distribution, I use a Continuous Normalizing Flow, using the "tricks'" of the FFJORD paper in order to improve the computational time of the normalizing term in the change of variable formula that is used to calculate the MLE of the NF. Changing from a discrete space of layers into a continuous space allows me to use more complex architectures using ODE Nets (NF has some constrains regarding the architecture to be used) and also improves the computational complexity I just mentioned.
RapidShare iOS app
November 1, 2013 – March 1, 2014
The RapidShare app allows users to view the files in their RapidShare accounts. Users can also take pictures and upload them directly to RapidShare, as well as upload pictures from their image libraries.
GOVoyages iOS App
June 1, 2013 – Present
Discover Travel: The booking your airline tickets on your iPhone! Now nothing easier to book an air ticket with confidence, wherever you are. Just set your criteria and our search engine will find you the best deals. For all flights, Govoyages guarantees you the lowest price! * The world in your pocket, it's simple as GO!
Opodo iOS App
January 1, 2013 – Present
Book your next flight with the new Opodo App >> One-way, return and multi-stop flight search >> Easy and secure booking process >> Automatically saves passenger and contact data to do your future bookings in seconds >> One click-to-call to contact Opodo support center >> Share interesting offers and your booked flights with friends >> All your trip info in the App with you always
eDreams iOS app
January 1, 2013 – October 1, 2013
eDreams is the largest independent european online travel agency. Its head-office is situated in Barcelona, Spain and it has also office in Italy. It focuses on offering the best selection of flights, hotels and vacation packages through the use of innovative search, packaging and booking engines via its websites (in English, French, Spanish, Italian, Portuguese, German and Turkish). Clients are offered all these services in a comfortable, simple manner through state-of-the-art booking and search engine technology. They include traditional airline and low cost flights, offering the best prices in the market to its clients. More than six million clients have reserved their hotels, flights and holiday package deals at eDreams since the company first started its activities. eDreams is the largest online travel agency in terms of sales in Southern Europe.
Fidiliti iOS app
September 1, 2012 – January 1, 2013
La misión de fidiliti es ayudar a las empresas a mejorar la comunicación empresa-cliente a través del uso de Smartphones. fidiliti, es una innovadora forma de fidelizar a los clientes mediante la virtualización de los programas de fidelización haciendo uso de los teléfonos smartphones.
wateqe iOS app
January 1, 2012 – June 1, 2012
wateqe is the first spanish social network exclusive for nightlife. With more than 2000 discos in the database, up to date, and ready to turn the heat on! , are you ready? wateqe is the difference between party and a MEGAPARTY. Blow up the night parties with wateqe. Compete with your friends to know who enjoy more and share your best pics in the community. Meet people around you inside the discos, discover if your friends are near to you and receive gifts for your loyalty. All this based on a UNIQUE technology designed for SMARTPHONES. (Nowadays available for Android&iPhone)
Practical Reinforcement Learning
Coursera
June 24, 2026 – Present
Bayesian Methods for Machine Learning
Coursera
June 24, 2026 – Present
Machine Learning Foundations: A Case Study Approach
Coursera Course Certificates
June 24, 2026 – Present
Machine Learning
Coursera Course Certificates
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a long tenure at Zattoo, first as an iOS Software Engineer and then transitioning to a Research/Machine Learning Engineer, which suggests loyalty and an ability to grow within an organization. The personal projects, especially the deep generative models and recommender systems, show a strong passion for the field beyond professional duties. The earlier career in mobile development, while not directly related to the target ML Engineer role, demonstrates a broad technical background. The diversity of projects (from travel apps to social networks) indicates adaptability, but the lack of explicit team collaboration or leadership roles in the descriptions limits the assessment of cultural fit in a collaborative ML environment.
Soft Skills & Operational Fit
The candidate's experience descriptions highlight problem analysis and communication skills. The detailed explanation of the 'Deep Generative Models' project suggests strong analytical thinking and a proactive approach to problem-solving. The transition from iOS development to ML engineering at the same company (Zattoo) indicates adaptability and a drive for continuous learning. However, without specific soft skill assessments or interview data, a comprehensive evaluation of operational fit is limited.