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Zalán – Typescript, React, Machine learning, experts in Lemon.io

Zalán

From Romania (UTC+3)

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Machine Learning EngineerMiddle-to-senior
Full-stack Web DeveloperSenior
8 years of commercial experience
AI
Art and creativity
Cloud computing
Construction
Cybersecurity
Energy
Entertainment
IoT
Machine learning
Smart home
Customer support software
Mobile apps

Zalán – Typescript, React, Machine learning

Zalán is a Senior full-stack developer with strong experience in React.js, Node.js, and TypeScript, complemented by a growing background in AI and LLM applications. He is skilled at building production-grade, AI-powered products, bringing practical experience in computer vision, generative AI, and backend engineering. Zalán is a quick learner with a problem-solving mindset, attentive to detail, and effective in teamwork and communication. With continued development in vector search, agent frameworks, and scalable LLM infrastructure, he is well-positioned to grow as a full-stack AI engineer, contributing end-to-end on modern, AI-integrated projects.

Main technologies
Typescript
6 years
React
6 years
Machine learning
4 years
AWS
3 years
Node.js
4 years
LLM
4 years
AI
4 years
JavaScript
6 years
Additional skills
Java
Python
DevOps
Docker
Linux
PostgreSQL
API
Next.js
Supabase
React Native
Git
Nest.js
MongoDB
Tailwind CSS
Stripe API
FastAPI
REST API
CI/CD
UI/UX
Spring Boot
Swift
PyTorch
OpenCV
Direct hire
Possible
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Experience Highlights

Head of Engineering / Full-stack Software Engineer / ML & DevSecOps Engineer
Jun 2023 - Jan 20251 year 7 months
Project Overview

This cutting-edge AI platform transforms text prompts, images, and sketches into high-quality visual content, serving both creative and professional users. It features a microservice-based architecture and a self-hosted solution for image generation, leveraging fine-tuned SDXL models and FLUX-based workflows to ensure scalability and efficiency.

Responsibilities:
  • Led and managed the backend development team while actively supporting the frontend team, ensuring seamless collaboration and efficient project execution to achieve milestones;
  • Planned, designed, and developed the architecture, infrastructure, and key features;
  • Facilitated communication and collaboration between QA, Content Management, Data Center representatives, and development teams to enhance workflow efficiency;
  • Interviewed and evaluated candidates for Backend and DevOps positions to expand the technical team;
  • Provided technical customer support and responded to technical inquiries on social media platforms;
  • Designed and optimized a scalable microservice architecture and migrated 150,000 users to a new platform;
  • Reduced infrastructure costs and enhanced image generation performance;
  • Launched a public API with a credit-based system and delivered a revamped UI/UX for a better user experience.
Project Tech stack:
Typescript
Next.js
i18next
Vercel
Tailwind CSS
shadcn
Stripe API
Auth0
Supabase
Pusher
MongoDB
MongooseODM
Nest.js
Python
FastAPI
Pydantic
AWS
Docker
Docker Compose
RabbitMQ
LLM
AI
Machine learning
Nginx
DevOps
GitHub
GitHub Actions
Linux
JWT
REST API
Node.js
Software Developer / DevSecOps Engineer
Sep 2019 - Nov 20223 years 2 months
Project Overview

This project is a microservice-based system designed to analyze and visualize log files generated by smart home controllers and cameras. It processes data to provide clear insights and real-time monitoring capabilities, helping users better understand the performance and status of their smart home devices. The architecture ensures scalability and efficient handling of large volumes of log data.

Responsibilities:
  • Managed the end-to-end development of a comprehensive microservices solution for managing log files of smart home devices;
  • Prioritized the implementation of high-security measures to safeguard sensitive data;
  • Designed the system to assist and expedite the workflow of the customer support service.
Project Tech stack:
Angular JS
Typescript
Next.js
Node.js
Java
Spring Boot
Spring Security
MongoDB
Splunk
Python
Jira
AWS
Terraform
Docker
Docker Compose
Software Engineer
Jul 2018 - Mar 20223 years 8 months
Project Overview

A cross-platform mobile application designed for service technicians to efficiently commission, configure, and maintain heating systems. The app streamlines setup processes, provides step-by-step guidance, and enables diagnostics for a wide range of heating devices, ensuring accurate and efficient field operations.

Responsibilities:
  • Designed, developed, and deployed a cross-platform mobile application for service technicians in the HVAC trade to support commissioning, repairing, and maintaining Junkers, Buderus, and Bosch heaters;
  • Reconstructed the application from Apache Cordova + AngularJS to React Native using a new design system;
  • Added support for new appliances and devices within the app;
  • Developed in-app purchase subscription functionality;
  • Built and maintained internal private React Native libraries to support app functionality and scalability.
Project Tech stack:
Angular JS
Apache Cordova
SCSS
JavaScript
Typescript
React Native
Objective C
Swift
Java
Python
AI Consultant
Jan 2021 - Aug 20216 months
Project Overview

A proctoring system designed to detect fraud during online exams, developed to support remote assessments in response to the pandemic. The platform ensures exam integrity by monitoring test-takers and identifying suspicious behaviors, enhancing the reliability of online evaluations for academic institutions.

Responsibilities:
  • Led research and development efforts to analyze market trends and integrate advanced computer vision techniques for fraud detection in live video streams, audio signals, and user behavior patterns;
  • Conducted thorough code reviews to enhance system performance, improve reliability, and ensure robustness in real-time monitoring environments;
  • Collaborated closely with cross-functional teams to implement cutting-edge algorithms aimed at identifying cheating behaviors during online examinations;
  • Focused on optimizing the detection system to operate efficiently under varying network conditions and hardware setups.
Project Tech stack:
Python
OpenCV
Keras
Tensorflow
PyTorch
Microservices
Software Engineer Intern
Sep 2017 - Jun 20191 year 9 months
Project Overview

Cross-platform dog breed identifier application developed as a Bachelor’s thesis project. The app uses image recognition technology to analyze user-uploaded photos and accurately identify various dog breeds. It provides an intuitive interface for users to easily access breed information on mobile devices, combining machine learning with mobile development to deliver a smooth and educational experience.

Responsibilities:
  • Designed, developed, and deployed a cross-platform mobile application working in both offline and online environments to identify dog breeds;
  • Planned, designed, and developed the architecture, infrastructure, and software system;
  • Researched innovative machine learning methods;
  • Trained, fine-tuned, and evaluated convolutional neural networks.
Project Tech stack:
JavaScript
React Native
Golang REST API
Python
Tensorflow
Docker
Docker Compose
Machine learning

Education

2018
Computer Science
BSc
2020
Data Analysis and Modelling
MSc

Languages

Romanian
Upper-intermediate
Hungarian
Advanced
English
Advanced

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