Hello there! I am

Diego Vaquero Melchor

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Senior Full Stack & Machine Learning Engineer with over 7 years of experience building scalable, data-driven products across mobile, cloud, and AI-powered platforms. Proven track record leading AI initiatives, architecting backend systems handling millions of daily requests, and bridging the gap between engineering and data science.

Holds a PhD in Technologies and Communication Systems, with strong expertise in recommender systems, cloud infrastructure, and immersive technologies such as AR and MR. Known for being a collaborative and uplifting teammate, fostering positive team dynamics and a strong work culture.

You have an idea, I have the knowledge to make it happen. Let's talk!

Studies

2017 - 2020

PhD in Technologies and Communications Systems

Universidad Politécnica de Madrid

Doctoral Thesis (Cum Laude): Technologies and Concepts for Enhancing Interaction and Enabling Collaboration in Augmented and Mixed Reality.

Focused on comparative user experience between wearable Augmented Reality (AR) and Mixed Reality (MR) devices versus conventional platforms.

Explored the appeal of 3D visualization in AR and the role of mid-air haptic feedback in improving interaction with digital content.

Investigated collaborative AR/MR applications, leading to the development of the SARA architecture, which enabled shared MR experiences across heterogeneous devices.

Proposed flexible Collaboration Models to streamline participant engagement and support the development of new multi-user MR experiences.

2014 - 2015

Master on Intelligent Systems

Universidad de Salamanca

2010 - 2014

Bachelor in Computer Science

Universidad de Salamanca

Work Experience

Nov 2023 - Present

Senior Full Stack and ML Engineer

Monkey Taps

Acted as the central point between full-stack engineering and data-driven ML/MLOps functions, bridging gaps and enhancing the integration of technology solutions.

A/B Testing System: Designed and implemented a remote A/B testing system that decoupled test operations from the mobile app release cycle, streamlining workflows and enabling faster releases.

Backend Infrastructure: Architected and implemented backend systems that served content to the mobile app, successfully handling 2M daily requests with an Appdex of 0.99.

Monitoring and Performance: Integrated New Relic for advanced monitoring and traceability of APIs, driving performance, stability, and security improvements across the platform.

Full Product Lifecycle: Contributed to all stages of the product lifecycle, from requirement gathering and implementation to long-term maintenance, ensuring robust solutions at every step.

Cloud Infrastructure: Managed and expanded cloud infrastructure using AWS technologies, including EC2, ElasticBeanstalk, Lambda, RDS, S3, Glue (for ETL processes), SQS, Athena (SQL queries for S3 data), and ElastiCache to ensure scalable, efficient systems.

Internal Admin Web Tool: Developed an internal admin web tool using Remix.js, enhancing team access to internal resources. Integrated a large language model (LLM) for auto-generating blog posts, increasing productivity and content creation speed.

AI Team Leadership: Led the AI team, driving alignment with product and business goals while providing technical guidance and ensuring successful implementation of AI solutions.

Custom ML Deployment Platform: Designed and implemented a custom platform for deploying ML and traditional models, allowing the data team to test multiple architectures simultaneously, leading to revenue growth and enhanced user experiences.

Recommendation System: Designed and implemented a recommendation system based on user interactions within the mobile app, increasing content engagement, favoriting, and driving subscription sales.

Apple Server-to-Server Integration: Created a solution for integrating Apple Server-to-Server notifications to improve winback strategies, providing better insights into subscription revenue and enabling more effective user engagement strategies.

Analytics & Traceability: Enhanced traceability and analytics across multiple company subsystems, such as the company blog, landing pages, and internal tools, improving decision-making and user insights.

Oct 2020 - Oct 2023

Machine Learning Engineer, Data Analyst and Full Stack Engineer

Wikifactory

Data Lake Architecture: Designed, implemented, and maintained a custom data lake tailored to company needs, aggregating information from internal databases and external services to support unified data access and analytics.

Data Analysis & Reporting: Managed data analysis and reporting workflows for multiple teams. Used SQL and BI tools like Metabase to deliver actionable insights and enable data-driven decision-making across the organization.

Recommendation System: Led the full development cycle of a content-based recommendation system leveraging embeddings. Also integrated GPT to detect and mitigate spam account creation, improving platform integrity.

Full Stack Development: Contributed to both frontend and backend platform development — utilizing React.js on the frontend and Flask on the backend — to support core product features.

OpenNext EU Project: Participated in the EU Horizon 2020 OpenNext project by implementing platform features that integrated partner microservices, fostering interoperability and collaboration between consortium members.

Jan 2017 - Jan 2020

PhD Student and Researcher

GPDS Group (Universidad Politécnica de Madrid)

Conducted research in Mixed Reality and Machine Learning applied to Smart Cities and UAV (Unmanned Aerial Vehicles) systems.

Worked on side projects involving remote airport control tower technologies.

Contributed to the design and development of immersive and intelligent systems aligned with real-world applications.

Supported thesis work focused on user interaction, collaboration models, and multi-user AR/MR experiences.

Nov 2015 - Dec 2016

Research Project Associate

MISO Group (Universidad Autónoma de Madrid)

Designed and developed a graphic editor for Domain Specific Languages (DSM), with special focus on mobile platforms.

Skills

Machine Learning & Data Science

Recommender Systems
TensorFlow
Keras
GPT/LLM Integration
Reinforcement Learning
Genetic Algorithms
Object Detection
Data Mining
Data Exploration
Bioinformatics
MLOps

Programming Languages

Python
JavaScript
Typescript
SQL
C#
Java

Frontend and Graphics

React
React Native
Remix.js
D3.js
Three.js
Unity 3D
Godot

Backend, Web and Databases

FastAPI
Flask
Supabase
Node.js
MySQL
PostgreSQL
MongoDB
Metabase
Docker

Cloud & DevOps

AWS (EC2, Lambda, S3, RDS, Glue, Elastic Beanstalk, SQS, Athena, ElastiCache)
Docker
Git
CI/CD
New Relic

AR/VR/MR, games and 3D Development

ARKit
Blender
Godot
Unity
Mixed Reality Toolkits

Project gallery

Machine Learning-based Content Recommender System

Developed a recommender system that suggests personalized content to users based on their textual data.

  • Built using embeddings architecture, training a model from scratch with public datasets.
  • Implemented with Python, Tensorflow, and Keras.
  • Integrated into the Wikifactory platform to enhance user experience.
  • Visualized resulting data using Tensorflow Projector and enabled querying via Python.

Python

Tensorflow

Keras

Recommender Systems

Embeddings

Content recommender

Ground Service

Created a microservice to generate heightmaps and terrain data for geospatial queries.

  • Extracted information from LAS files, particularly from the Spanish IGN (Instituto Geográfico Nacional).
  • Generated tile matrices with heightmaps and RGB ground color data.
  • Produced minimum heightmap images for given coordinates.
  • Future layers can include machine learning annotations for features like buildings, water, and forests.

Node.js

Tree.js

GIS

Microservices

3D

Image processing

SARA: An Architecture for Shared-Augmented Reality Experiences and Applications

Designed an architecture enabling collaborative AR applications across diverse devices.

  • Supported cross-platform, multi-user Augmented Reality collaboration.
  • Highly scalable with on-the-fly collaboration model changes.
  • Allowed users to define custom collaboration models.
  • Integrated into Blender via an addon to inject 3D scenes into SARA sessions.

Node.js

C#

Javascript

HoloLens

Unity 3D

MRTK

iOS

ARKit

Microservices

HARP: An Architecture for Haptically Enhanced AR Experiences

Developed an architecture to enhance AR 3D content perception with haptic feedback.

  • Explored the concept of haptics to improve user interaction.
  • Implemented as an additional layer over the SARA architecture.

C#

HoloLens

Unity 3D

MRTK

UHDK5

UltraHaptics

Wearable AR

HCI

Mid-air

HMD

Mission Definition System Web Editor

Built a web application for visually creating and automating drone flight missions.

  • Enabled users to define multiple geometrical inspections.
  • Allowed specification of takeoff and landing points for missions.
  • Generated trajectory estimations based on inspection shapes.
  • Integrated real-world geospatial information into the system.

Javascript

Three.js

jQuery

MongoDB

GIS

A Distributed Drone-Oriented Architecture for In-Flight Object Detection

Developed a cloud-based architecture for real-time video streaming and object detection.

  • Supported multiple drone types with real-time video streaming.
  • Showcased capabilities through a telecommunication tower inspection use case.
  • Enabled real-time model switching and combination for object detection.

Python

Tensorflow

D3.js

CNNs

Real-time

Object Detection

Machine Learning

DSL-Comet: A Domain-Specific Language Visual Editor

Developed an iOS tool for graphical and collaborative modeling on mobile devices.

  • Enabled creation of both Sirius and mobile editors from a single description.
  • Supported local and server-based model storage compatible with EMF.
  • Integrated geographic information into models.

iOS

Node.js

MongoDB

Mongoose

DSL

Data Mining from the International Cancer Genome Consortium

Applied clustering techniques to uncover relationships in human genome mutation catalogs.

  • Identified clusters with the 12 most mutated gene families across three projects.
  • Highlighted 5 cytobands for future studies on liver cancer development.
  • Developed a tool to visualize mutation positions within human chromosomes.

Clustering

Processing

Three.js

Java

Data Analysis

Data Visualization

Publications

Technologies and concepts for enhancing interaction and enabling collaboration in augmented and mixed reality. Doctoral thesis

Diego Vaquero-Melchor

https://doi.org/10.20868/UPM.thesis.65850

2020

Link

SARA: A Microservice-Based Architecture for Cross-Platform Collaborative Augmented Reality

Diego Vaquero-Melchor, Ana M. Bernardos, Luca Bergesio

Applied Sciences, 10(6), 2074

2020

Link

Enhancing Interaction with Augmented Reality through Mid-Air Haptic Feedback: Architecture Design and User Feedback

Diego Vaquero-Melchor, Ana M. Bernardos

Applied Sciences 9 (23), 5123

2019

Link

Alternative interaction techniques for drone-based mission definition: from desktop UI to wearable AR

Diego Vaquero-Melchor, Ana M. Bernardos

MUM 2019: 51:1-51:5

2019

Link

Drones-as-a-service: A management architecture to provide mission planning, resource brokerage and operation support for fleets of drones

Juan A. Besada, Ana M. Bernardos, Luca Bergesio, Diego Vaquero-Melchor, Iván Campaña, José R. Casar

PerCom Workshops 2019: 931-936

2019

Link

Drone Mission Definition and Implementation for Automated Infrastructure Inspection Using Airborne

Juan A. Besada, Luca Bergesio, Iván Campaña, Diego Vaquero-Melchor, Jaime López-Araquistain, Ana M. Bernardos, José R. Casar

Sensors 18(4): 1170 (2018)

2018

Link

A Distributed Drone-Oriented Architecture for In-Flight Object Detection

Diego Vaquero-Melchor, Iván Campaña, Ana M. Bernardos, Luca Bergesio, Juan A. Besada

HAIS 2018: 433-445

2018

Link

Holo-mis: a mixed reality based drone mission definition system

Diego Vaquero-Melchor, Jorge García-Hospital, Ana M. Bernardos, Juan A. Besada, José R. Casar

MobileHCI Adjunct 2018: 365-370

2018

Link

Active Domain-Specific Languages: Making Every Mobile User a Modeller

Diego Vaquero-Melchor, Javier Palomares, Esther Guerra, Juan de Lara

MoDELS 2017: 75-82

2017

Link

Towards Enabling Mobile Domain-specific Modelling

Diego Vaquero-Melchor, Antonio Garmendia, Esther Guerra, Juan de Lara

ICSOFT-PT 2016: 117-122

2016

Link

Domain-Specific Modelling Using Mobile Devices

Diego Vaquero-Melchor, Antonio Garmendia, Esther Guerra, Juan de Lara

ICSOFT (Selected Papers) 2016: 221-238

2016

Link

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