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Schedule Interview NowVladislav H. - Ml Engineer, AI Agent Development, Research & Strategy
My name is Vladislav H. and I have over 5 years years of experience in the tech industry. I specialize in the following technologies: Real Estate Marketing, Trading Automation, Financial Software, Real Estate, Automation, etc.. I hold a degree in Bachelor of Computer Science (BCompSc), , , High school degree. Some of the notable projects I’ve worked on include: : : ☎️ Ai Prospecting Application (FreeSwitch, KeyCloack, Twilio), : : 🌿 (Ai & SaaS) - Mint Real Estate Group., : : 🏡 (Ai) & Software Architecture.. I am based in Barcelona, Spain. I've successfully completed 3 projects while developing at Softaims.
I'm committed to continuous learning, always striving to stay current with the latest industry trends and technical methodologies. My work is driven by a genuine passion for solving complex, real-world challenges through creative and highly effective solutions. Through close collaboration with cross-functional teams, I've consistently helped businesses optimize critical processes, significantly improve user experiences, and build robust, scalable systems designed to last.
My professional philosophy is truly holistic: the goal isn't just to execute a task, but to deeply understand the project's broader business context. I place a high priority on user-centered design, maintaining rigorous quality standards, and directly achieving business goals—ensuring the solutions I build are technically sound and perfectly aligned with the client's vision. This rigorous approach is a hallmark of the development standards at Softaims.
Ultimately, my focus is on delivering measurable impact. I aim to contribute to impactful projects that directly help organizations grow and thrive in today’s highly competitive landscape. I look forward to continuing to drive success for clients as a key professional at Softaims.
Main technologies
Ml Engineer
5 years
Real Estate Marketing
1 Year
Trading Automation
4 Years
Financial Software
4 Years
Additional skills
- Real Estate Marketing
- Trading Automation
- Financial Software
- Real Estate
- Automation
- Scripts & Utilities
- Web Development
- Real Estate IDX
- Product Development
- Artificial Intelligence
- Neural Network
- Machine Learning
- Generative AI
- AI Agent Development
- Research & Strategy
Direct hire
Potentially possible
Experience Highlights
: : ☎️ Ai Prospecting Application (FreeSwitch, KeyCloack, Twilio)
AI Prospecting Application - enriched prospects, agentic workflows, and smart, personalized outbound.
: : 🌿 (Ai & SaaS) - Mint Real Estate Group.
As a software developer, I had the possibility of working on a project for Mint Real Estate Group, a prestigious real estate brokerage in Spain. The project involved the development of a comprehensive website, property management app, and import management Cross-CRM system, with the goal of providing clients with an unparalleled user experience while accessing the company's extensive portfolio of over 80,000 properties. One of the unique challenges I encountered was the differing naming conventions used by the CRM systems - Resales Online, Inmoba, Inmovilla, and Expo Costa Del Sol - each having different category and local urban name conventions. This resulted in duplicate properties with varying image quality and descriptions. However, leveraging expertise in advanced deep learning algorithms to develop an efficient solution that facilitated the identification and merging of similar properties, resulting in a unified database that eliminated duplicates. To create a responsive and unique user interface, I used technologies such as Type-Script, Nest JS, and Next JS. I also implemented GraphQL as a flexible and efficient query language for APIs and MongoDB as a scalable and high-performance NoSQL database system for data storage and retrieval. To ensure the scalability and application orchestration of the website, I utilized Docker for containerization, Nginx for load balancing, reverse proxying, and caching, and Redis for caching and message brokering. I customized the solutions to meet Mint Real Estate Group's specific needs, including an efficient and user-friendly property management app, an import management cross-CRM system that seamlessly integrated data from multiple CRM systems, a visually appealing and easy-to-navigate responsive user interface, and advanced deep learning algorithms to identify and merge duplicate property listings in the database. Overall, this project showcases my expertise in utilizing advanced technologies and customized solutions to deliver a comprehensive and user-friendly real estate property management system. : : Core Technologies: · Python: · Utilized as the primary programming language for machine learning development. · JavaScript (TypeScript): · Leveraged for front-end development, enhancing code readability and maintainability. · Nest JS: · A progressive Node.js framework employed for building efficient, scalable, and maintainable · server-side applications. · Next JS: · A powerful React framework used for server-rendered React applications, optimizing performance and user experience. · GraphQL: · Implemented as a flexible and efficient query language for APIs, enabling precise data fetching and real-time updates. · MongoDB: · A scalable and high-performance No-SQL database system used for data storage and retrieval. : : Application Orchestration: · Docker: · Utilized for containerization, streamlining the deployment process and ensuring consistency across environments. · Nginx: · A high-performance web server employed for load balancing, reverse proxying, and caching, improving overall application performance. · Redis: · An in-memory data store used for caching and message brokering, enhancing application responsiveness and scalability. *and more...
: : 🏡 (Ai) & Software Architecture.
I had the pleasure of working on a real estate project that demonstrated the potential of natural language processing and deep learning. My task was to integrate data from various sources and develop a user-friendly property search experience for potential buyers. To accomplish this, I employed a variety of technologies including Python, JavaScript (Type-Script), Nest JS, Next JS, GraphQL, and MongoDB. This allowed me to overcome the challenge of integrating data from four distinct CRM systems (Resales Online, Inmoba, Inmovilla, and Expo Costa Del Sol) and create a search engine that seamlessly queries more than 80,000 properties. To ensure consistency and performance, I used Docker for containerization, Nginx for load balancing, reverse proxying, and caching, and Redis for caching and message brokering. This improved application responsiveness and scalability, resulting in a robust user experience. In addition, I integrated deep learning architecture to enhance image analysis. This included analyzing image similarity properties such as depth, geometry, pixel nucleus, and image features, as well as property description analysis. I created a unique algorithm to enhance images and provide a distinctive photo shot style, offering clients a more immersive property viewing experience. Overall, this project is a prime example of how AI and software architecture can integrate data from multiple sources to improve user experiences in the real estate industry. The project also demonstrates the potential of natural language processing and deep learning. I am proud to have contributed to this project and the successful results achieved.
Education
Formación Profesional - Jorge Guillen
Bachelor of Computer Science (BCompSc) in Computer science
2012-01-01-2016-01-01
Lewagon
in Full-Stack Development (Ruby)
2021-01-01-2021-01-01
Ironhack Barcelona
in Full-Stack Development (JavaScript)
2020-01-01-2020-01-01
IES Alfaguar
High school degree in High School Math, Science and Engineering
2008-01-01-2012-01-01
Languages
- English
- Spanish
- Ukrainian
Github