Alex Brad, Developer in London, United Kingdom
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Alex Brad

Verified Expert  in Engineering

Software Developer

London, United Kingdom
Toptal Member Since
April 16, 2020

Alex is a software engineer, hacker, AI breeder, data wrestler, and web app blacksmith. But most of all, he is a problem solver. He thrives on new challenges, whether algorithmic or even the occasional bug-hunting—he likes debugging. With a solid background in machine learning and full-stack engineering, he is currently focusing on the domain of AI applications using LLMs.


Freelance Clients
ChatGPT, OpenAI API, JavaScript, Python, Pinecone
Freelance Clients
Python, JavaScript, Scraping, APIs, Machine Learning, Blockchain, Data Analysis...
Non-disclosed Hedge Fund
HTML, Python, Web Scraping, Data Analysis, Web, JavaScript, CSS, HTML5...




Preferred Environment

Python, JavaScript

The most amazing...

...thing I've built was a price elasticity prediction model for tier 1 airlines based on unstructured web data related to events.

Work Experience

Software Engineer and GPT Specialist

2022 - PRESENT
Freelance Clients
  • Developed an app that enables the users to upload PDF files and ask questions based on the contents of the file. ChatGPT API was used for this together with Pinecone for embeddings indexing.
  • Built a tool for text classification and sentiment analysis using ChatGPT API.
  • Developed a counseling chatbot (using ChatGPT API) that helps people see other people's points of view.
Technologies: ChatGPT, OpenAI API, JavaScript, Python, Pinecone

Software Engineer

2021 - 2022
Freelance Clients
  • Collected transaction data for cryptocurrencies from various APIs.
  • Built automated tools to gather data from social groups related to cryptocurrencies.
  • Extracted and processed data from the Ethereum blockchain to understand activity about various smart contracts.
  • Analyzed Solidity code to understand various smart contracts better.
  • Built and maintained data pipelines to transform and aggregate the gathered data.
  • Conducted data analysis to identify the usefulness of data in predicting trading patterns for various cryptocurrencies.
  • Developed a web app for complex data exploration and visualization.
  • Built predictive models for trading activity in various cryptocurrencies.
  • Experimented with algorithmic trading of cryptocurrencies.
Technologies: Python, JavaScript, Scraping, APIs, Machine Learning, Blockchain, Data Analysis, Amazon Web Services (AWS), MongoDB, Data Visualization, Interactive Charts, Ethereum, Web3.js, Ethers.js, Solidity, Full-stack, Third-party APIs, Front-end, Web Scraping, Git, Data Engineering, Data Mining, REST, GPT, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), Unit Testing, Object-oriented Programming (OOP), Functional Programming, REST APIs, Databases, Web Crawlers, Regex, NoSQL, Amazon S3 (AWS S3), Amazon EC2, Web Development, GitHub, Next.js, API Integration, Financial Data, Fintech, XML, Full-stack Development

Software Engineer

2020 - 2021
Non-disclosed Hedge Fund
  • Researched and identified potential indicators for the economic activity of various companies.
  • Built complex automated scraping tools to gather data related to these indicators regularly.
  • Created and maintained a custom data pipeline to collect, transform, and aggregate the data related to the indicators.
  • Designed and built a modular system where data sources could be easily added or swapped.
  • Defined the research workflow and managed two other doing research and scraper implementation.
  • Developed a web application for the visualization and interpretation of the gathered data.
  • Built an automated system for anomaly detection in the gathered data.
Technologies: HTML, Python, Web Scraping, Data Analysis, Web, JavaScript, CSS, HTML5, Amazon Web Services (AWS), MongoDB, Full-stack, Front-end, Git, Scraping, Data Engineering, REST, Unit Testing, Object-oriented Programming (OOP), Functional Programming, REST APIs, Databases, Web Crawlers, Regex, NoSQL, Amazon S3 (AWS S3), Amazon EC2, Web Development, GitHub, API Integration, Financial Data, Fintech, Stock Market, Full-stack Development, Selenium, Automation

Machine Learning Engineer

2018 - 2020
  • Built the infrastructure for collecting structured and unstructured data from the web and social media.
  • Used NLP techniques to extract events from unstructured text and understand their importance.
  • Created data processing pipelines using Python and Spark.
  • Explored, visualized, and cleaned up airline data using Pandas and Matplotlib.
  • Developed machine learning models for assessing event importance, predicting travel demand, and price sensitivity.
  • Built a web app for showing important events and their impact on travel using React and Redux.
  • Deployed data pipelines and web apps on Google Cloud and AWS using Docker and Kubernetes.
  • Mentored other developers on full-stack and machine-learning topics.
Technologies: MongoDB, JavaScript, Machine Learning, Web Scraping, Front-end, Third-party APIs, Full-stack, React, Scrapy, Kubernetes, Docker, Spark, XGBoost, Scikit-learn, Pandas, Jupyter, Python, Git, Scraping, E2E Testing, Data Engineering, Data Mining, REST, Generative Pre-trained Transformers (GPT), Natural Language Processing (NLP), GPT, Unit Testing, Object-oriented Programming (OOP), Functional Programming, REST APIs, SQL, Databases, Web Crawlers, Regex, NoSQL, Amazon S3 (AWS S3), Amazon EC2, Web Development, GitHub, API Integration, XML, Full-stack Development, Artificial Intelligence (AI)

Full-stack Developer

2014 - 2017
  • Designed and implemented a small CMS using Express.js.
  • Developed responsive websites using the CMS mentioned above.
  • Extracted and processed data from 3rd-party APIs, including Facebook, Google Maps, Eventbrite, and Meetup.
  • Scraped websites and processed data about events or places.
  • Developed mobile apps using Ionic, Cordova, and Parse.
  • Deployed and maintained apps and websites on Parse, AWS, and Heroku.
  • Designed, implemented, and interpreted complex analytics using Google Analytics.
  • Designed and implemented, in collaboration with an on-site team, several components in a complex web ERP framework built with Angular and .NET.
  • Researched and proposed architectural changes for the framework mentioned above.
Technologies: Web Scraping, Front-end, Third-party APIs, Full-stack, Google Analytics, Heroku, Ionic, MongoDB, Node.js, Express.js, Angular, CSS, HTML, JavaScript, Git, REST, SCSS, Unit Testing, Functional Programming, SQL, jQuery, Databases, Regex, NoSQL, Amazon S3 (AWS S3), Web Development, GitHub, XML, Full-stack Development, Minimum Viable Product (MVP), Firebase

Front-end Developer

2014 - 2014
  • Chose the technology stack and created the architecture for the single-page application developed in Angular.
  • Designed and implemented a WYSIWYG blog editor using vanilla JavaScript.
  • Designed and implemented a tool for semantically annotating an HTML article.
  • Refactored and extended a legacy Knockout.js application.
Technologies: Front-end, Angular, Bootstrap, CSS, HTML5, JavaScript, Git, Databases, Web Development, GitHub

Co-founder and Developer

2012 - 2013
  • Identified financing opportunities and drafted a business plan.
  • Pivoted several times to identify the most suitable MVP.
  • Researched and employed linked data standards and libraries.
  • Extended Backbone.js to build a framework to handle semantic data dynamically.
  • Used 3rd-party APIs to gather data and integrate content.
Technologies: Front-end, Apache Jena, RDF, Java, JavaScript, Git, Databases, GitHub, XML, Minimum Viable Product (MVP)

Automated System for Cryptocurrency Data

An automated system for gathering, processing, and exploring cryptocurrency-related data. The data was gathered from various sources, text data from social groups, trading data from APIs, and data extracted from the blockchain.

Built a React web app for data exploration and visualization involving interactive charts and drill-down workflows. I was the sole developer for the project and led the research, design, and implementation of the end-to-end solution.

Automated Data Gathering System

The drive behind the project was to be able to gather publicly available data that might indicate the economic activity of various public and private companies.

This involved a lot of research to identify potential indicators and then building automated scrapers to gather that data regularly. This would sometimes involve a lot of complexity because the workflows required to generate data were not straightforward.

The architectural focus of the system was to be very modular, so adding or replacing new data sources would be as straightforward as possible. Additionally, the system included a pipeline for transforming, validating, and aggregating the gathered data.

Initially, I managed the design and building of the system from scratch. Later on, when two additional people were onboarded, I was responsible for defining the research and data-gathering workflow and supervising the work of the two additional team members.

Predicting Travel Demand and Price Sensitivity

At Migacore, we've built a product that can help predict the impact of events on Airline demand and price sensitivity based on data mined from the web.

In short, our approach involved crawling structured and unstructured data to extract multiple data points related to events. These were later used to understand which events impact travel and what that impact is likely concerning demand and price sensitivity.

Migacore is a small startup, so I was involved in most areas of research and implementation, including:
• Building several scrapers to collect structured and unstructured data from the web.
• Working on the data pipeline that ingested this data, used Named Entity Extraction for isolating events, and assigned additional data points to events.
• Designing and training models to filter down many events to a subset of potentially relevant ones.
• Processing, exploring, and cleaning-up airline data.
• Designing and training models to predict the actual impact of the events on demand and price sensitivity.
• Mentoring other developers.
• Collaborating in building a web app and deploying our models and pipeline in a Kubernetes cluster.

Semantic Travel Blogging

Recognos had an in-house project for Semantic Travel Blogging. This involved using named entity recognition and sentiment analysis to identify and rank accommodations, restaurants, attractions, and activities.

I was in charge of the architecture for the web app and was involved only sparingly in the back-end NLP work. In addition to acting as a usual blogging platform, the app also had to provide tools for manually annotating text, which I built from scratch.

I also created a WYSIWYG web text editor inspired by the one Medium had at the time because none of the existing open-source ones satisfied our requirements.


HTML, SCSS, Python, JavaScript, SQL, HTML5, CSS, XML, ECMAScript (ES6), Regex, TypeScript, Java, RDF, Solidity


Scrapy, Redux, Jest, Flask, Angular, Express.js, Bootstrap, Hadoop, Apache Jena, Ionic, Spark, AngularJS, Next.js, Selenium


REST APIs, Scikit-learn, Pandas, jQuery, React Redux, XGBoost, Node.js, React, NumPy, Matplotlib, Keras, Natural Language Toolkit (NLTK), TensorFlow, Web3.js


Git, Jupyter, GitHub, Seaborn, Google Analytics


Unit Testing, Object-oriented Programming (OOP), Functional Programming, REST, E2E Testing, ETL, Data Science, Automation


Web, Amazon EC2, Linux, Docker, Heroku, Amazon Web Services (AWS), Jupyter Notebook, Kubernetes, Google Cloud Platform (GCP), Blockchain, Ethereum, Firebase


MongoDB, Amazon S3 (AWS S3), Redis, Databases, NoSQL, Data Pipelines, AllegroGraph


APIs, Third-party APIs, Front-end, Algorithms, Data Analysis, Data Visualization, Gradient Boosted Trees, Data Engineering, Web Scraping, Full-stack, Scraping, Software Engineering, Web Development, API Integration, Web Crawlers, Artificial Intelligence (AI), Data Mining, Natural Language Processing (NLP), Machine Learning, Interactive Charts, GPT, Generative Pre-trained Transformers (GPT), Cordova, Deep Learning, Ethers.js, Neural Networks, Financial Data, Fintech, Stock Market, Full-stack Development, Minimum Viable Product (MVP), ChatGPT, OpenAI API, Pinecone

2010 - 2012

Master's Degree in Intelligent Systems

Babes-Bolyai University - Cluj-Napoca, Romania

2007 - 2010

Bachelor's Degree in Computer Science

Babes-Bolyai University - Cluj-Napoca, Romania


Cambridge English | Proficiency (CPE)

Cambridge Assessment English