About the Company:
ModaTrend Digital is Pakistan’s leading fashion-tech retailer offering AI-driven size prediction, virtual try-on capabilities, and a nationwide digital apparel marketplace. The company leverages data science and modern AI to transform the online fashion experience.

Location: Karachi, Sindh, Pakistan
Employment Type: Full-time
Experience Level: Mid to Senior-level (4–7 years)

Role Overview:
As an AI Personalization & Recommendation Engineer, you will build, train, and optimize recommendation models that personalize user experience and increase product relevance across ModaTrend’s platform. Your work will directly impact customer satisfaction, engagement, and conversion rates.

Key Responsibilities:
• Design and develop recommendation engines using machine learning and deep learning.
• Build personalization pipelines based on user behavior, size data, browsing trends, and preferences.
• Implement A/B tests to evaluate model performance and tuning.
• Work with large-scale fashion datasets to improve search relevance and product ranking.
• Collaborate with backend engineers to integrate models into production systems.
• Enhance the virtual try-on recommendation logic using AI-driven insights.
• Monitor model drift, retrain models, and ensure performance benchmarks.
• Document research findings and improvements for ongoing optimization.

Qualifications:
• Bachelor’s or Master’s degree in CS, AI, or Data Science.
• 4–7 years of experience building ML-based recommendation systems.
• Expertise in Python, TensorFlow/PyTorch, and data pipelines.
• Strong understanding of recommendation algorithms (collaborative filtering, deep ranking models).
• Experience with cloud deployment on AWS/GCP/Azure.
• Excellent analytical and problem-solving skills.

What We Offer:
• Opportunity to build AI systems for one of Pakistan’s top fashion-tech brands.
• Access to high-quality fashion datasets and modern ML infrastructure.
• Professional AI development training and conference participation.
• Cross-functional collaboration with fashion designers, engineers, and data scientists.