Technical lead-Backend Engineering

Myntra Engineering

The Myntra Engineering team develops the technology platform that drives our customers' shopping experience and ensures the efficient movement of products from suppliers to their final destinations. Our work spans a variety of areas, including building massive-scale web applications, creating engaging user interfaces, developing big-data analytics, mobile apps, workflow systems, and inventory management solutions. As a lean technology team, every individual's contribution is significant. You will have the chance to be part of a rapidly expanding organization and gain comprehensive exposure to all components of a complete e-commerce platform.

About the Team - Ad Tech Platform

The Ad Tech Platform team at Myntra builds the engine that powers millions of shopping experiences daily and helps thousands of sellers to give visibility to their products and help in generating revenue. We are a high-impact, fast-paced group of engineers sitting at the intersection of massive-scale distributed systems and advanced machine learning. As we evolve our infrastructure, we are moving beyond traditional ad-serving to pioneer the next generation of product discovery, heavily investing in semantic search and vector databases to enhance ad relevance. Our culture is defined by deep technical ownership, high-scale engineering excellence, and a collaborative spirit that bridges the gap between production software and data science. Joining us means solving some of the most complex challenges in e-commerce at scale, working with a team that values innovation, reliability, and technical craft.

Key Responsibilities

• Design & Architecture: Lead the end-to-end design, architecture, and implementation of complex, high-scale distributed ad-serving systems. Ensure high availability, low latency, and reliability using Java, Kafka, Redis, and Aerospike.
• ML Pipelines & Online Serving: Design, code, troubleshoot, and support scalable ML pipelines and online model-serving systems for the ad platform — from data ingestion and feature engineering through training to real-time, low-latency inference within the ad-serving path.
• ML Integration & Strategy: Bridge the gap between Data Science and Engineering. Own the productionization of ad ranking and response-prediction models (CTR/CVR), ensuring experimental models from the DS team are seamlessly integrated, scalable, and performant in production. Work hand-in-hand with data scientists to optimize model performance and the underlying ML infrastructure.
• Search Innovation: Spearhead the migration and optimization of our search infrastructure. Lead the implementation and fine-tuning of semantic search capabilities and vector databases to significantly improve ad relevance.