Jr. AI Design Intelligence Engineer

BLUDIGIT TECHNOLOGIES

Pune, India

1-3 Years

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Posted 2 days ago
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Job Description

Role Overview

We are building an AI-powered textile design generator and processor focused on screen printing workflows. This role is centered on deep research, understanding user intent, and translating design requirements into AI-driven outputs.

As an AI Research & Design Intelligence Engineer, you will act as the bridge between users (designers, printing units, brands) and the AI systems that generate textile designs. Your primary responsibility is to understand what users want, why they want it, and how that requirement can be best delivered through AI models, prompts, and pipelines.

This is a full-time, entry-level role (1.5+ years experience) with heavy emphasis on research, experimentation, learning, and iteration.

Core Responsibilities

1. User Research & Requirement Understanding

Study and analyze user needs across textile designers, screen printers, and apparel brands.
Break down vague or creative requests (e.g., ethnic but modern, export-friendly floral, budget print design) into structured AI-understandable inputs.
Identify patterns in user requests and convert them into reusable design logic, workflows, and AI strategies.
Work closely with stakeholders to document design intent, constraints, and output expectations.

2. Textile Design Research (India-Focused)

Research, document, and categorize Indian textile styles, motifs, textures, and color systems used across regions, markets, and price segments.
Build a structured design knowledge base (styles, occasions, markets, printing constraints).
Translate traditional textile knowledge into AI-friendly classifications and metadata.

3. Dataset Strategy & Design Intelligence

Design and maintain high-quality textile image datasets aligned with user needs and printing realities.
Define dataset structure based on design purpose, not just volume (e.g., commercial prints vs. fashion-forward designs).
Continuously refine datasets based on user feedback and output quality.

4. AI Model Selection & Management (Decision-Oriented)

Design and maintain a Python-based AI management system that selects the most suitable AI model based on:
User intent
Design complexity
Style requirements
Cost and latency constraints
Research strengths and limitations of different image generation and processing models and map them to real-world use cases.

5. Prompt Engineering & Design Translation

Convert user requirements into enterprise-grade prompts that reliably produce usable textile designs.
Experiment with prompt structures to improve:
Style accuracy
Repeatability
Print suitability
Build prompt templates and libraries based on common user design needs.

6. AI Training, Fine-Tuning & Validation

Fine-tune and train models using domain-specific textile datasets.
Evaluate AI outputs against user expectations and commercial usability, not just visual quality.
Iterate models and prompts based on real feedback from designers or printing workflows.

7. Cost Optimization & Practical AI Strategy

Research and implement cost-efficient AI generation strategies.
Decide when:
A large model is needed
A smaller or fine-tuned model is sufficient
Balance quality vs. cost based on user requirements and business goals.

8. Continuous Research & Technology Awareness

Stay updated with latest AI models, research papers, and tools relevant to generative design.
Evaluate new technologies based on practical usefulness, not hype.
Work with the development team to implement promising AI advancements.

Required Skills & Background

Must-Have

1.5+ years of experience in AI/ML, data science, or software development.
Strong research mindset ability to explore, experiment, and document findings.
Proficiency in Python.
Curiosity to understand design thinking and user behavior, even without a formal design background.

Preferred (Not Mandatory)