Software Engineer at Sagital.ai

Developed Neo, a generative AI platform that automates software engineering tasks, boosting team productivity by reducing manual coding. Built full-stack features with Node.js back end APIs and React dashboards. Integrated LLM-powered AI features for automated code review, Q&A, and task recommendations. Optimized database queries, API endpoints, and caching to improve performance and response times. Implemented authentication, RBAC, and secure data handling for enterprise users. Collaborated with product managers and engineers to refine features based on pilot user feedback. Designed monitoring and logging pipelines to track AI model performance and user interactions. Contributed to CI/CD pipelines to automate testing, deployment, and model updates. Introduced model monitoring to ensure AI predictions remain accurate in production.

Designed and deployed AI-powered NLP solutions for clients, including intent recognition and text summarization. Fine-tuned large language models for client-specific applications, improving accuracy by 15–20%. Implemented automation pipelines that reduced manual preprocessing time by 50%. Designed and deployed AI-powered NLP solutions integrated into web applications with React and Node.js. Fine-tuned LLMs for client-specific use cases, improving task accuracy by 15–20%. Built automated ETL pipelines for preprocessing unstructured text and structured data. Implemented RESTful APIs for AI services, supporting multiple client applications. Developed interactive dashboards to visualize AI outputs, model metrics, and performance analytics. Collaborated with clients to define requirements, deploy solutions, and provide technical guidance.

Senior Machine Learning/NLP Engineer at Wluper

Led NLP initiatives focused on conversational AI, dialogue systems, and intent classification. Designed and deployed ML models into production with robust evaluation pipelines. Improved intent recognition accuracy by 18% through advanced model architecture and feature engineering. Mentored junior ML engineers and collaborated with product teams to align AI solutions with business goals. Led NLP projects including intent recognition, dialogue systems, and conversational AI platforms. Designed, trained, and deployed ML models into production using Python, PyTorch, and Node.js backend services. Improved intent recognition accuracy by 18% through feature engineering and model tuning. Built pipelines for text preprocessing, tokenization, embedding generation, and model inference. Worked closely with frontend teams to integrate AI models with React-based dashboards. Mentored junior ML engineers, providing guidance on model design, data preparation, and coding best practices. Implemented perf

C#.NET Developer at Kingspan Group

Developed internal software applications using C# and .NET, enhancing system reliability. Built and maintained backend services, APIs, and data workflows for internal business operations. Automated repetitive tasks and workflows, reducing manual intervention and errors.

Software Engineer at Sagital.ai

Developed Neo, a generative AI platform automating software engineering tasks, enhancing team productivity by reducing manual coding tasks. Built full-stack features using Node.js for back-end APIs and React for dashboards. Integrated LLM-powered AI features for automated code review, Q&A, and task recommendations. Optimized queries, endpoints, caching, and implemented authentication and RBAC for enterprise users.

Senior Machine Learning/NLP Engineer at Wluper

Led NLP initiatives focused on conversational AI, dialogue systems, and intent classification. Designed and deployed ML models to production with robust evaluation pipelines. Improved intent recognition accuracy by 18% through feature engineering and model tuning. Mentored junior ML engineers and collaborated with product teams to align AI solutions with business goals.

Machine Learning/NLP Engineer at Wluper

Built NLP pipelines for text processing, recognition, and production deployment using Python, PyTorch, and Node.js backend services. Developed pipelines for data preprocessing, tokenization, embeddings, and model inference. Coordinated with frontend teams to integrate AI models with React dashboards; implemented monitoring and automated retraining for production models.

C# .NET Developer at Kingspan Group

Developed internal software applications using C# and .NET, enhancing system reliability. Built and maintained backend services, APIs, and data workflows for internal operations; automated repetitive tasks to reduce manual intervention and errors.