AI Intern

7 days ago

Surat, 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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