Gustavo Muller, Developer in Curitiba - State of Paraná, Brazil
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Gustavo Muller

Verified Expert  in Engineering

Back-end Developer

Curitiba - State of Paraná, Brazil
Toptal Member Since
February 24, 2021

Gustavo is a goal-driven back-end developer with over 20 years of experience in AI, embedded devices/apps, machine vision, and high-performance network client/server software. Gustavo's expert skillset includes a range of languages (Python, C++, JavaScript), tools (Visual Studio), and platforms (Linux, Windows). Gustavo's held several leadership roles—including CTO, CIO, development manager—as well as technical roles to deliver several solutions, as seen in his project history.


Python, Heroku, Django, Vue, Amazon Web Services (AWS), REST APIs, Bootstrap...
C, C++, Assembly, PostgreSQL, Amazon Web Services (AWS), C#, Java, .NET, Azure...
Consilux Tecnologia
Apache Cassandra, C++, C, Python, Transmission Control Protocol (TCP), UDP...




Preferred Environment

Django, C++, OpenCV, Vue, Node.js, Java, TensorFlow, Python, JavaScript

The most amazing...

...thing I've developed was machine-vision software capable of recognizing car license plates and car models which enabled millions of dollars in cost savings.

Work Experience


2021 - PRESENT
  • Developed the assessment tools used by students and board advisors to evaluate companies (built with Django and Vue.js).
  • Designed and oversaw ERP and CRM implementation; also implemented the IT process and privacy policies in compliance with Brazilian laws.
  • Designed and oversaw the evolution of the company's website portal, CMS, and LMS platform to version 2.0. The aim is to impact over 1,000,000 Brazilian companies by 2023.
Technologies: Python, Heroku, Django, Vue, Amazon Web Services (AWS), REST APIs, Bootstrap, JavaScript, CSS, Back-end


2011 - 2019
  • Idealized, implemented, and managed the company's entire technology strategic plan as well as its products and services. This work enabled the company to become a leader in its field with over 300,000 tracked assets.
  • Built one of the biggest proprietary RF networks for asset tracking using technologies like ad-hoc LoRa and Sigfox with over 200,000 antennas.
  • Developed a leading UBI platform using AI, big data, and a high-performance scalable platform (AWS). The platform was used by 12 of the biggest auto insurance companies in Brazil and included customized mobile apps with gamification.
  • Developed a fleet management-and-optimization web platform using cutting-edge web-and-mobile technologies.
  • Maintained, refactored, integrated, and managed ERP and CRM ecosystems like SAP, OutSystems, and Salesforce.
  • Developed and deployed an efficient field-servicing AI platform to route technicians nationwide—allowing the throughput of 40,000 service orders per month.
  • Constructed a highly available, scalable, and reliable IT infrastructure that supported all IT operations; it's 100% cloud-based on AWS/Azure supporting 24/7 call center operations with over 300 agents and a multi-terabyte data warehouse.
  • Managed the PMO team and all IT services including outsourcing, structure, and development; Scrum, Kanban, and squads were the main methodologies used.
  • Led the development of a middleware payment platform with different e-payments and gateways systems like (Stone, Cielo, MercadoPago, PagSeguro). The system processed all credit card regular and recurring payments.
Technologies: C, C++, Assembly, PostgreSQL, Amazon Web Services (AWS), C#, Java, .NET, Azure, Python, Node.js, Ionic, OutSystems, Django, JavaScript, Docker, Vue, React, SQLite, Amazon DynamoDB, Amazon S3 (AWS S3), AWS Lambda, Back-end

Development Manager

2009 - 2011
Consilux Tecnologia
  • Developed and maintained a vehicle-tracking software platform that enabled the company to enter the asset tracking market; it went from 0 to 20,000 tracked assets in two years.
  • Led a team of developers in the analysis and rebuild of software from conception through implementation using Agile methods such as Scrum.
  • Managed all employees which included coaching, training, and performance-improvement action plans.
  • Developed vehicle-tracking and fleet-management software from the ground up.
  • Migrated an on-premise infrastructure to a cloud infrastructure (AWS) that facilitated a 30% reduction in costs.
  • Led the relocation of the datacenter and operations to VMware ESXi instances which enabled further scalability and flexibility for the company.
  • Developed innovative tracking device features in the Brazilian market that promoted fast business growth. Some of these features were used by accelerometers to sense vehicle movement.
Technologies: Apache Cassandra, C++, C, Python, Transmission Control Protocol (TCP), UDP, Thread Scheduling, Linux, VPN, MongoDB, PostgreSQL, C#, Java, Amazon Web Services (AWS), VMware ESXi

Development Engineer

2005 - 2009
Consilux Tecnologia
  • Built intelligent transportation systems (ITS) including traffic counting sensors, speed enforcement devices, and dynamic traffic light controllers with fuzzy logic. The AI was used to optimize green light timing and improved traffic speed by 30%.
  • Created traffic counting devices using pneumatic sensors (embedded C and Microcontroller Assembly).
  • Developed the communication layer used by all company software (TCP/IP and UDP/IP). The communication stack used real-time compression and cryptography with over 1,000 clients using the communication library.
  • Constructed short-range RF transmission systems to send and receive data from the speed enforcement devices.
  • Developed a web-based, speed-enforcement fines-processing system using Java (JSP).
  • Implemented embedded systems for police forces with a range of features, including GPS navigation, routing, service dispatches, and license plate recognition.
Technologies: C, C++, Assembly, TCP/IP, UDP, Delphi, Fuzzy Logic, Convolutional Neural Networks (CNN), Pattern Matching, Python

Engineering Trainee

2002 - 2005
Consilux Tecnologia
  • Developed automatic license plate recognition software that enabled an over 80% in cost savings to the company. The tech used neural nets and machine vision C/C++ algorithms to convert images into readable characters.
  • Built traffic counting and speed enforcement devices using low-level Assembly and C for microcontrollers.
  • Created machine vision systems such as face detection and recognition using Haar-like features and OpenCV.
Technologies: Delphi, C, Assembly, C++, OCR, Machine Learning, Neural Networks, Machine Vision, OpenCV

Programmer Analyst Trainee

2001 - 2001
OG Net
  • Developed all the TCP/IP stack used by the company's main apps using Delphi and C++.
  • Built an intelligent ads system similar to Google Ads. The system was able to collect data from the user and display contextualized ads.
  • Created a hook app that collected all the user's typed words and categorized them in a SQL database for later classification and use.
Technologies: Delphi, C++, TCP/IP

Automatic License Plate Recognition

I developed this algorithm from scratch. There were no AI libraries available at that time, so everything has to be implemented on your own.

The software used machine vision algorithms like image opening, closing, filling, and Sobel filtering to find possible candidates for plate regions. Candidates were classified by aspect ratios and the number of elements.

The neural network was an RNN implemented in C and converted the image characters into text. The algorithm achieved up to 90% effectiveness in recognizing car plates for speed enforcement.

UBI Platform

Usage Based Insurance (UBI) was the client and a leader in their field in Brazil, and I led a team of developers and engineers in the development of their platform.

The platform collected data from over 300,000 tracked vehicles and sent the data to AWS servers that processed the data using big data technologies. We had over 1TB of data to be processed into individual driver behavior models. The result was a driving score that measured how prone the car was to get into an accident. The client then sold this information to insurance companies.

The technology involved many clever AI, including neural networks and machine learning algorithms, to achieve this. The end-user was able to consume this data using mobile applications (iOS/Android).

Trading Signal Alerts

I developed an automatic trading platform to dispatch trading signals when they occur. The idea was to use known trading setups and let the software monitor multiple tickers and timeframes. When the trading condition is met, we then dispatch a trading signal to a website.

I used MetaTrader to implement the logic to detect the trading signals and SQLite to store them locally and a Python application to replicate data to the cloud. Once in the cloud, the data is consumed by a Vue.js-based website using a REST API built with Django.

The app monitors over 100 tickers in five different timeframes each, and we implemented over ten trading setups.
2018 - 2019

Master's Degree in Business Administration

Pontificia Universidade Catolica do Rio Grande do Sul - Porto Alegre, Brazil

2005 - 2007

Master's Degree in Business Administration

FAE Business School - Curitiba, Brazil

2000 - 2004

Engineer's Degree in Electrical Engineering

Universidade Federal do Paraná - Curitiba, Brazil


Node.js, OpenCV, Vue, TensorFlow, React, REST APIs, PyTorch


Visual Studio, VPN


Python, C++, Embedded C++, Delphi, Java, Assembly, SQL, JavaScript, C, C#, CSS


Ubuntu Linux, Windows, Apache Kafka, Firebase, Linux, Amazon Web Services (AWS), Azure, Docker, Heroku, AWS Lambda, MetaTrader 5


Django, .NET, Ionic, Bootstrap, React Native, Hadoop


Agile, MapReduce


PostgreSQL, MongoDB, SQLite, Amazon DynamoDB, Amazon S3 (AWS S3)

Industry Expertise

Telecommunications, Project Management


Business Planning, Business Administration, Team Management, Back-end, Electronics, Artificial Intelligence (AI), Business Analysis, Innovation, 2D Games, Full-stack, TCP/IP, OCR, Machine Learning, Neural Networks, Machine Vision, UDP, Fuzzy Logic, Convolutional Neural Networks (CNN), Pattern Matching, Apache Cassandra, Transmission Control Protocol (TCP), Thread Scheduling, VMware ESXi, OutSystems, Amazon Kinesis

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