Software Engineer Engineering

Darshan Raja

AI/ML Data Scientist Software Engineer

Summary

• AI/ML Engineer with 2+ years of experience in Large Language Models (LLMs), Machine Learning, Generative AI, and full-stack software engineering, with a Master’s in Information Technology (Data Science concentration) at UNC Charlotte (GPA 4.0).

• Currently leading development of a Railway Traffic Management System (RTMS), designing an automatic train routing system using WPF (Caliburn.Micro MVVM, Material Design), SQL Server persistence (EF Core, ADO.NET, UPSERT/MERGE), and event-driven logging, with a proposed multi-tenant AWS deployment (ECS Fargate, RDS, Cognito, Secrets Manager) for scalability and tenant-aware isolation.

• Built and deployed LLM-powered applications, including ChatGPT-4 text bots and Retrieval-Augmented Generation (RAG) pipelines, enabling conversational AI, intelligent automation, and knowledge retrieval across custom datasets.

• Designed predictive healthcare models for ICU length of stay, heart disease detection, and driver etiquette monitoring, applying interpretable AI techniques (SHAP, LIME, PDP) to improve trust and explainability.

• Skilled in building end-to-end ML pipelines with Python, PyTorch, TensorFlow, Scikit-learn, OpenCV, and deploying on Azure and AWS with CUDA acceleration and MLOps practices.

• Experienced in 3D computer vision and texture generation workflows, integrating Blender automation, OpenCV, and PyTorch for high-fidelity 3D asset creation.

• Strong communicator and collaborator with proven ability to bridge AI research, LLMs, cloud architecture, and enterprise software engineering, delivering impactful, production-grade solutions. Technical Skill Set

Programming Languages

Python, C++, C, Java, C#, JavaScript, Dart, SQL

AI/ML Frameworks

PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, Hugging Face Transformers, OpenCV, SHAP, LIME, PDP LLMs & GenAI

ChatGPT-4, Retrieval-Augmented Generation (RAG)

pipelines, LangChain, Prompt Engineering, Text Bots, Generative AI workflows

Data & Visualization Pandas, NumPy, Matplotlib, Seaborn, Tableau Databases

SQL Server, MySQL, PostgreSQL, MongoDB, Firebase,

Oracle

Cloud & MLOps

Microsoft Azure (VMs, CUDA), AWS (EC2, S3, RDS,

Cognito, ECS Fargate, Secrets Manager), Snowflake, MLflow, Kubeflow, Airflow

Software Engineering

WPF (Caliburn.Micro, Material Design), ADO.NET,

Entity Framework Core, AutoMapper, Git, Jupyter, Google Colab, Anaconda, Spring Boot, IntelliJ, Jira

Specialized Domains

CAD-style editors, Automatic Train Routing (RTMS), 3D Computer Vision, Blender Automation, Cloud Deployment Architecture

Professional Experience

Computer Data/Software Engineer — Railway Transport Management Solutions (RTMS), Fort Worth, TX

Jun 2025 – Present

• Leading development of an automatic train routing system, improving routing efficiency by 35% through optimized algorithms and CAD-style editor enhancements.

• Designed a modular, layered WPF client (Caliburn.Micro MVVM, Material Design) supporting CAD-style editing of tracks, switches, signals, and control points, which reduced design time by 25% for operators.

• Integrated SQL Server persistence with UPSERT logic (MERGE) to synchronize CAD edits, cutting data sync errors by 40% and ensuring reliable JSON metadata storage.

• Built event-driven logging to capture real-time updates, reducing debugging turnaround by 30% and improving auditing transparency.

• Applied dependency injection, AutoMapper, structured logging, and comprehensive unit testing, increasing maintainability and cutting bug resolution time by 20%.

• Proposed a multi-tenant AWS deployment model (ECS Fargate, RDS, Cognito, Secrets Manager) projected to improve system scalability by 50% while ensuring tenant-aware security. AI/ML Engineer — CFG Software Pvt Ltd – Charlotte, NC Jan 2025 – May 2025

• Designed and deployed GANs and CNNs for 3D asset generation, improving rendering realism by 25% (94% PSMR accuracy benchmark).

• Optimized ML pipelines using Python, PyTorch, TensorFlow, and OpenCV, reducing training/runtime by 30%and debugging overhead by 20%.

• Scaled deep learning workloads on Azure CUDA VMs, achieving a 40% increase in training efficiency and enabling multi-dataset experiments.

• Integrated Hugging Face Transformers into facial reconstruction pipelines, reducing fine-tuning time by 20%across diverse datasets.

• Built RAG pipelines leveraging LLMs for automated asset tagging and code documentation, cutting manual annotation time by 35%.

• Developed GUI plugins for Unity and Unreal Engine, accelerating internal adoption of AI-driven 3D tools by 50% and reducing asset iteration cycles.

• Implemented automated testing suites (unit + integration) for ML workflows, lowering post-deployment errors by 15%.

• Deployed models into production using CI/CD pipelines, MLflow, and Docker, ensuring reproducibility and version tracking.

• Applied structured logging, monitoring, and alerting to track model drift and runtime failures, improving issue resolution speed by 30%.

• Collaborated with cross-functional teams (design, data, cloud) to align ML models with product requirements, reducing handoff delays by 20% and improving release cycles. Software Associate — Indium Software Pvt Ltd – Chennai, India Feb 2023 – Nov 2023

• Developed a university recommendation system using ML algorithms, improving placement prediction accuracy by 22%.

• Built data pipelines to clean and process student datasets, cutting preprocessing time by 30%.

• Automated Jira lifecycle management workflows, reducing manual reporting effort by 40%.

• Designed and deployed cloud-ready microservices with load-balancing, reducing downtime by 15%.

• Integrated SQL databases with backend APIs, improving query efficiency by 25%.

• Built RESTful APIs with Spring Boot/Java, improving backend maintainability and reusability.

• Conducted unit testing and debugging to ensure stable deployments, lowering bug reports by 18%.

• Collaborated with product and QA teams, shortening sprint release cycles by 20%. Software Developer Intern — Phoreuia Pvt Ltd – Kochi, India Nov 2022 – Jan 2023

• Developed a speech recognition model (96% accuracy) for warehouse operators using deep learning.

• Built real-time processing pipelines with Python and TensorFlow, reducing request latency by 28%.

• Integrated model into automation workflows, increasing operational throughput by 20%.

• Implemented unit testing for speech modules, cutting post-deployment failures by 15%.

• Deployed models with Docker + CI/CD pipelines, ensuring consistency across environments.

• Wrote structured logs for error tracing, improving debugging efficiency by 25%. Software Developer Intern — Cirus Labs Pvt Ltd – Bangalore, India Apr 2022 – May 2022

• Contributed to design of cloud-based enterprise software with scaling and load-balancing features.

• Assisted in implementing multi-cloud deployments (AWS + Azure), improving redundancy by 15%.

• Built database integration layers with SQL + NoSQL, improving data retrieval efficiency.

• Participated in unit testing and QA cycles, reducing integration defects by 10%.

• Documented system architecture and workflows, improving onboarding speed for new hires by 20%. AI Projects & Research

• Developed LLM-powered chatbots using ChatGPT-4 + RAG pipelines, enabling conversational AI and intelligent document retrieval with a 35% reduction in manual search time.

• Built predictive healthcare models for ICU length of stay and heart disease detection, improving prediction accuracy by 18% using interpretable AI (SHAP, LIME, PDP).

• Designed a Driver Etiquette Detection System (Computer Vision + NLP + Flutter app), published in IEEE Xplore, achieving 92% classification accuracy. -

• Automated 3D texture generation pipelines in Blender using Python, OpenCV, PyTorch, reducing manual modeling effort by 40%.

Education

University of North Carolina at Charlotte (UNCC) — Charlotte, NC Master of Science in Information Technology — Concentration: Data Science Jan 2024 – May 2025 GPA: 4.0 / 4.0

Kumaraguru College of Technology — Coimbatore, India Bachelor of Engineering in Information Science and Engineering Aug 2019 – Apr 2023 GPA: 3.52 / 4.0

Certifications

• AWS Certified Cloud Practitioner (CLF-C02) – View Certificate

• AWS Solutions Architect Associate - View Certificate

• Fundamentals of Visualization with Tableau – View Certificate

• Agile with Atlassian Jira – View Certificate

• Flutter with Dart – View Certificate

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