AI Intern

2 days ago

tamil nadu, India ManageArtworks Full time

About Karomi   ManageArtworks (A flagship product brought to you by Karomi, a leading Enterprise SaaS provider) enables 4000 leading Global and Indian brands. We offer everything to get artwork projects going & manage every step of the packaging and artwork process. Companies reach markets faster with our end-end packaging & artwork management system while achieving 100% compliance.  Project Duration:  2 Months  Location:  Chennai – On Site  Overview   We are enhancing an AI-powered packaging artwork design platform  for FMCG and pharmaceutical clients that automates the creation of compliant, visually appealing packaging designs. The role focuses on building an intelligent layout engine  that uses Large Language Models (LLMs) , domain-specific design heuristics, layout intelligence, and visual reasoning to determine optimal placement of text, symbols, and imagery. This system aims to streamline creative workflows while ensuring regulatory compliance and delivering high-quality, automated artwork generation.  Key Deliverables   Design and implement an AI-driven artwork layout engine  capable of interpreting textual and visual input to determine placement of design elements.  Build LLM-based modules  that understand packaging copy content, regulatory zones, and design intent.  Develop rule-based and heuristic models  for spacing, hierarchy, and alignment of packaging components (e.g., ingredients, logos, nutrition tables, symbols).  Integrate vision and layout analysis models  (e.g., LayoutLM, Detectron2, or similar architectures) to map artwork panels and guide composition.  Combine text-to-layout reasoning  (LLM) with visual placement algorithms  for adaptive artwork generation.  Implement and integrate the layout engine into existing Flask/FastAPI  microservices for seamless deployment in production.  Build evaluation pipelines for layout quality, visual balance, and compliance metrics.  Document model architecture, placement logic, heuristics, and integration strategy for both technical and product teams.  Desired Candidate Profile   Must-Have Skills   Strong programming skills in Python   Knowledge of LLMs  and prompt engineering  for reasoning tasks  Experience in Computer Vision  and Natural Language Processing (NLP)   Experience with rule-based heuristics  or constraint-based design optimization  Understanding of packaging artwork workflows  and regulated content placement (food, pharma, or FMCG)  Proficiency in PyTorch/TensorFlow  for custom model development  Exposure to Flask/FastAPI  integration and API-based architectures  Experience with vector/geometry libraries  (e.g., Shapely, OpenCV) for layout computation  Strong debugging and rapid prototyping capabilities  Good-to-Have Skills   Familiarity with Generative AI for design automation  (text-to-image or layout synthesis)  Background in graphic design principles , typography, and visual hierarchy  Knowledge of SVG/PDF parsing and rendering  for artwork files  Outcome   A functional AI-powered layout automation engine  capable of generating packaging artworks with minimal manual intervention  Integration of LLM reasoning + heuristic rules + vision models  for intelligent design placement  Improved design turnaround time  and regulatory compliance consistency   Technical proof-of-concepts for automated artwork design and layout generation   Recommendations for scaling the system into a full design automation product  

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