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I am a Software Engineer and AI researcher currently based in Ireland, with experience spanning industry, academia, and applied research. I am presently working at Technological University Dublin, where I focus on large language models, model compression, and system-level AI integration. My research includes Tailored-LLaMA, a structured pruning and task-specific prompting framework that retains high accuracy while significantly reducing model size, which I presented at ECAI 2024. Previously, I worked as a Software Engineer at Teradata, contributing to ModelOps platforms using Spring Boot, Angular, Docker, and PostgreSQL, and earlier as a Machine Learning Engineer at Vidizmo, where I optimized deep learning models for video analytics. I have also completed a software engineering internship at Autodesk, building AI-driven sustainability tools that integrate large-scale environmental datasets to support low-carbon construction decisions. My interests lie at the intersection of LLM efficiency, applied machine learning, and real-world AI systems, with multiple peer-reviewed publications in top venues including IEEE TIP, CVPR Workshops, and ECAI. I enjoy translating advanced research into practical, scalable solutions with measurable impact.…I am a Software Engineer and AI researcher currently based in Ireland, with experience spanning industry, academia, and applied research. I am presently working at Technological University Dublin, where I focus on large language models, model compression, and system-level AI integration. My research includes Tailored-LLaMA, a structured pruning and task-specific prompting framework that retains high accuracy while significantly reducing model size, which I presented at ECAI 2024. Previously, I worked as a Software Engineer at Teradata, contributing to ModelOps platforms using Spring Boot, Angular, Docker, and PostgreSQL, and earlier as a Machine Learning Engineer at Vidizmo, where I optimized deep learning models for video analytics. I have also completed a software engineering internship at Autodesk, building AI-driven sustainability tools that integrate large-scale environmental datasets to support low-carbon construction decisions. My interests lie at the intersection of LLM efficiency, applied machine learning, and real-world AI systems, with multiple peer-reviewed publications in top venues including IEEE TIP, CVPR Workshops, and ECAI. I enjoy translating advanced research into practical, scalable solutions with measurable impact.

Danyal Aftab

Data Scientist, AI Engineer, Full Stack Developer, +3

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I am a Software Engineer and AI researcher currently based in Ireland, with experience spanning industry, academia, and applied research. I am presently working at Technological University Dublin, where I focus on large language models, model compression, and system-level AI integration. My research includes Tailored-LLaMA, a structured pruning and task-specific prompting framework that retains high accuracy while significantly reducing model size, which I presented at ECAI 2024. Previously, I worked as a Software Engineer at Teradata, contributing to ModelOps platforms using Spring Boot, Angular, Docker, and PostgreSQL, and earlier as a Machine Learning Engineer at Vidizmo, where I optimized deep learning models for video analytics. I have also completed a software engineering internship at Autodesk, building AI-driven sustainability tools that integrate large-scale environmental datasets to support low-carbon construction decisions. My interests lie at the intersection of LLM efficiency, applied machine learning, and real-world AI systems, with multiple peer-reviewed publications in top venues including IEEE TIP, CVPR Workshops, and ECAI. I enjoy translating advanced research into practical, scalable solutions with measurable impact.…I am a Software Engineer and AI researcher currently based in Ireland, with experience spanning industry, academia, and applied research. I am presently working at Technological University Dublin, where I focus on large language models, model compression, and system-level AI integration. My research includes Tailored-LLaMA, a structured pruning and task-specific prompting framework that retains high accuracy while significantly reducing model size, which I presented at ECAI 2024. Previously, I worked as a Software Engineer at Teradata, contributing to ModelOps platforms using Spring Boot, Angular, Docker, and PostgreSQL, and earlier as a Machine Learning Engineer at Vidizmo, where I optimized deep learning models for video analytics. I have also completed a software engineering internship at Autodesk, building AI-driven sustainability tools that integrate large-scale environmental datasets to support low-carbon construction decisions. My interests lie at the intersection of LLM efficiency, applied machine learning, and real-world AI systems, with multiple peer-reviewed publications in top venues including IEEE TIP, CVPR Workshops, and ECAI. I enjoy translating advanced research into practical, scalable solutions with measurable impact.

Available to hire

I am a Software Engineer and AI researcher currently based in Ireland, with experience spanning industry, academia, and applied research. I am presently working at Technological University Dublin, where I focus on large language models, model compression, and system-level AI integration. My research includes Tailored-LLaMA, a structured pruning and task-specific prompting framework that retains high accuracy while significantly reducing model size, which I presented at ECAI 2024.

Previously, I worked as a Software Engineer at Teradata, contributing to ModelOps platforms using Spring Boot, Angular, Docker, and PostgreSQL, and earlier as a Machine Learning Engineer at Vidizmo, where I optimized deep learning models for video analytics. I have also completed a software engineering internship at Autodesk, building AI-driven sustainability tools that integrate large-scale environmental datasets to support low-carbon construction decisions.

My interests lie at the intersection of LLM efficiency, applied machine learning, and real-world AI systems, with multiple peer-reviewed publications in top venues including IEEE TIP, CVPR Workshops, and ECAI. I enjoy translating advanced research into practical, scalable solutions with measurable impact.

Skills

Experience Level

Expert

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Intermediate

Intermediate

Work Experience

Senior software Engineer at Technological University Dublin

November 1, 2025 - Present

Designed and deployed a high-performance Model Context Protocol (MCP) server for Anyscore, enabling secure and real-time access to sports analytics data. Integrated the MCP server with LibraChat MCP client using the Azure GPT-5 API to support natural-language queries over complex datasets. Enabled advanced match-insight generation including player performance metrics, team statistics, and tactical breakdowns, increasing analytical depth. Automated data-analysis workflows, reducing processing time by more than 75% and improving efficiency across the analytics team.

Intern, Software Engineer |Pset - Developer Enablement at Autodesk

July 1, 2025 - September 1, 2025

Developed an AI-driven sustainability application by implementing an MCP server, enabling LLMs to access real-time environmental data for construction materials and support low-carbon strategies using a serverless architecture. Built an Idemat connector within the Sustainability Data API to integrate with the Idemat database, handling over 3,000 Environmental Product Declarations (EPDs). Delivered measurable business impact by reducing material sustainability research time from hours to seconds, empowering architects and engineers with data-driven carbon footprint analysis, and facilitating low-emission material selection throughout the construction process.

Software Engineer at Teradata

September 1, 2021 - September 1, 2023

Worked on backend and frontend for ModelOps application using Angular, Spring Boot framework, and PostgreSQL database. Design and develop RESTful web services using Spring Data REST, JDBC and Hibernate Framework. Utilize JMS and ActiveMQ to create a Train, Evaluate, and Deployment job that runs inside a docker container. Write automated test suites using JUnit, Cucumber JVM, and Cypress testing frameworks. Worked on automating data science workflows by utilizing Python, shell scripts, and Dockerfile in the pipeline. Added the support for import, evaluate, and deploy models (SAS, PMML, and ONNX) in the application. Implement UI components and services using Angular Material, NGX Bootstrap, and Covalent libraries. Work with the engineering team to create and evaluate new features, product ideas and technical designs. Utilize Git, Maven, and JIRA for version control, build, and deployment processes. Optimize application by refactoring and removing technical debt from the codebase.

Machine Learning Engineer at Vidizmo

June 1, 2021 - August 1, 2021

Develop and maintain the backend of Vidizmo product using the .NET framework and MySQL database. Develop and implement REST APIs. Create content processing workflows for video and AI processing. Integrate deep learning-based models in enterprise application. Optimized object detection models for videos using TensorRT. Perform unit testing of developed modules and systems. Prepare the dataset for Yolov5 model by translating anchor box coordinates. Worked in an Agile development methodology and participated in daily stand-up meetings and sprint reviews.

Teaching Assistant at National University Of Computer And Emerging Science

October 1, 2020 - March 1, 2021

Teaching assistant for Database Systems (CS203) and Operating Systems (CS205) courses; provided support to a class of 50 students, conducted office hours, graded assignments, and supported course instruction.

Software Engineer at Technological University Dublin

November 1, 2025 - Present

Designed and deployed a high-performance Model Context Protocol (MCP) server for Anyscore enabling secure, real-time access to sports analytics data; integrated MCP server with LibraChat MCP client configured with the Azure GPT-5 API to support natural-language data queries; automated data-analysis workflows, reducing processing time by over 75% and enhancing analytics efficiency.

Intern, Software Engineer at Autodesk

July 1, 2025 - September 1, 2025

Implemented an MCP server to enable LLMs to access real-time environmental data for construction materials; built an Idemat connector within the Sustainability Data API handling 3,000+ Environmental Product Declarations; reduced material sustainability research time from hours to seconds, enabling data-driven carbon footprint analysis and low-emission material selection.