Software engineering · ML systems
I build and evaluate systems involving model inference, collaborative state, graph algorithms, computer-vision pipelines, and performance-sensitive backend services.
1846 / 1848
Peak contest ratings
CodeChef / LeetCode
93.7%
VoiceGIS parser accuracy
538 reproducible cases
10 / 1,000
Collaboration convergence
Clients / randomized operations
C++ → WASM
CashFlow solver
Optional matching runtime
Multi-page vision
NiftyBooks internship
Generation and editing workflows
Selected engineering work
Four case studies focused on architecture, constraints, correctness, failure behaviour, and measured evidence. AI is presented as one component—not as a substitute for system design.
Collaborative systems · Flagship case study
A multi-user architecture-modelling engine with granular Yjs graph state, board-scoped authorization, durable updates, deterministic graph analysis, and reproducible infrastructure exports.
Convergence verified across 10 clients and 1,000 randomized operations.
Professional work · Computer vision
A multi-stage story illustration and character-editing workflow spanning scene decomposition, consistent generation, character matching, editable masks, and region-based edits.
Owned integration across inference, editing, asset handling, and post-processing failure paths.
Published library · Evaluation-driven
A voice interaction layer for Leaflet and OpenLayers with pluggable speech engines, custom commands, middleware, chaining, undo/redo, and a reproducible parser benchmark.
93.7% accuracy across 538 command-parser cases.
Algorithms · Full-stack systems
A group-expense and settlement platform using integer-cent accounting, exact small-group optimization, a deterministic fallback, permissions, audit records, exports, and live updates.
Exact minimum-payment search for up to 12 non-zero balances.
Additional work
Kept visible for breadth, with claims intentionally scoped to what each project demonstrates.
Engineering experiment
An exploration of deterministic IFC geometry extraction with IfcOpenShell and agent-assisted analysis over structured building data.
Interface experiment
A browser drawing interface connected to an image-generation workflow for turning rough sketches into illustrated outputs.
Engineering notes
Reproducible tests, algorithm boundaries, and evaluation methods behind the featured work.
Distributed state · 8 min read
A seeded harness for duplicates, delayed delivery, reordering, local undo, restart recovery, and canonical state comparison.
Algorithms · 9 min read
Why fixed-point money matters, where exact minimum-payment search becomes expensive, and how to design a deterministic fallback.
Evaluation · 7 min read
Building an offline benchmark that separates parser coverage from speech recognition and makes regressions reproducible in CI.
Experience
01 / Aug 2025 — Present
Mönchengladbach, Germany · Remote
NiftyBooks FlexCo
Building and integrating multi-stage computer-vision workflows for story illustration and cross-image character editing.
02 / Jun 2024 — Jul 2024
Remote
TECOSYS
Integrated external AI-processing endpoints into a web product and translated client workflows into maintainable frontend and backend changes.
03 / May 2023 — Jul 2023
Gurugram, Haryana · Remote
DIGINIQUE TECHLABS (iHUB)
Contributed to a restaurant software project across backend implementation, data handling, and interface delivery.
Engineering focus
Technologies are listed where they are supported by work shown in the case studies.
About
I am a Computer Science graduate and AI Engineer Intern at NiftyBooks FlexCo. My work has focused on multimodal generation systems, computer-vision workflows, model-serving APIs, and human-in-the-loop editing tools.
Outside my internship, I build systems involving real-time collaboration, graph algorithms, WebAssembly, geospatial interfaces, and reproducible evaluation. I am particularly interested in software engineering and machine-learning engineering roles where correctness, performance, and system behaviour matter as much as the user interface.
Contact
I am currently considering Software Engineering, Machine Learning Engineering, Computer Vision, and ML Infrastructure opportunities.