Rahul R

R&D Engineer with hands-on experience building and deploying machine learning, deep learning, and NLP-driven systems in production. A fast, self-driven learner who quickly picks up new technologies and frameworks and turns them into working, production-grade solutions. Skilled in end-to-end backend development and deployment, transformer-based document intelligence, computer vision (OCR), and conversational AI.

Proven track record reverse engineering complex applications, architecting scalable backend pipelines, and shipping ML-powered features from research to production.

R&D Engineer - Ninestars Information Technologies Pvt. Ltd.

(2025-07)

• Owned complete backend development and deployment for AOTM DSX, a next-generation design automation and intelligent layout platform, from architecture through production release.
• Reverse engineered proprietary and third-party desktop-publishing applications and file formats to enable automated parsing, manipulation, and interoperability within the platform.
• Built and shipped a conversational AI chatbot that automates packaging artwork creation from scratch, translating natural-language briefs into structured, print-ready design output.
• Rapidly learned and adopted new tools, frameworks, and techniques as project needs evolved, independently ramping up on unfamiliar tech stacks and shipping production-ready implementations.
• Researched and implemented transformer-based deep learning models to automate document layout generation and content understanding, improving processing efficiency by ~40%.
• Designed and optimized image processing pipelines for document segmentation, OCR enhancement, and layout analysis using Python and OpenCV.
• Engineered algorithms for XML-based design template extraction and manipulation, powering scalable desktop-publishing automation.
• Integrated AI/ML and NLP components with proprietary design tools to enable intelligent formatting, structure recognition, and automated content placement.
• Designed and evaluated deep learning workflows for layout structure prediction from scanned documents and PDFs.
• Designed and implemented the backend data layer for the AOTM DSX platform, including schema design and query optimization for managing design assets, templates, and project metadata.
• Built a file management system supporting versioning, storage, and retrieval of design files and assets across the platform, ensuring reliable access for concurrent editing workflows.
• Implemented role-based user access control and permissions management, enabling secure multi-user collaboration and controlled access to projects, templates, and assets.
• Architected database schemas and access patterns to support scalable storage of design templates, user data, and application state across the DSX platform.

R&D Intern - Ninestars Information Technologies Pvt. Ltd.

(2025-01 - 2025-07)

• Explored and evaluated open-source and proprietary desktop-publishing file formats to assess feasibility of automated parsing for the AOTM DSX platform.
• Prototyped image preprocessing techniques (denoising, thresholding, contour detection) to support early-stage OCR and layout analysis experiments.
• Assisted in benchmarking transformer-based models for document understanding tasks, documenting accuracy and performance trade-offs.
• Investigated XML schema structures used in design templates to understand extraction feasibility for downstream automation.
• Built small proof-of-concept scripts to test database schema designs for storing template and asset metadata.
• Participated in code reviews and technical discussions, gaining exposure to production-grade backend practices.
• Documented research findings and technical experiments to support the team's decision-making on tooling and architecture choices.

AI Data Trainer - Invisible Technologies

(2024-12 - 2025-01)

• Annotated and labeled multi-modal datasets (text, image, audio) to train and validate AI/ML models.
• Ensured 99% data labeling accuracy through strict quality assurance and validation protocols.
• Interpreted evolving project guidelines and adapted annotation workflows to meet client requirements.
• Collaborated with cross-functional teams to optimize labeling strategies, improving model precision by ~15%.
• Identified edge cases, flagged inconsistencies, and provided actionable feedback to enhance data quality.
• Maintained high productivity, data integrity, and confidentiality throughout large-scale labeling projects.
• Participated in pilot tasks to refine AI training pipelines and improve dataset usability.

10th Grade - CBSE - Maharishi Vidya Mandir, Hosur (2017 - 2018)

12th Grade - CBSE - Sri Chaitanya Techno School, Bangalore (2019 - 2020)

M.Tech Integrated - Computer Science Engineering with Spec. in Data Science - Vellore Institute of Technology, Vellore (2020 - 2025)