SDE II, Amazon India Ads

Job description

If you are excited by the opportunity to build highly innovative, scalable, high-performance, and low-latency solutions at the intersection of digital advertising and AI/ML, this may be the right career move for you. Be part of an innovative and passionate team leveraging generative AI, large language models, and advanced machine learning to build a successful, sustainable, and strategic international advertising business for Amazon, from the ground up.

Key job responsibilities

You will design and build large-scale ML infrastructure for online recommendation, ads ranking, personalization, and search — including integrating generative AI and LLM-based approaches to improve ad relevance and customer experience.

You will work with modern AI/ML and Big Data technologies such as AWS (SageMaker, Bedrock, EMR), Spark, PyTorch/TensorFlow, vector databases, LLM serving frameworks, and real-time inference pipelines.

You will drive appropriate technology choices for the business — evaluating when to apply traditional ML vs. foundation models, leading continuous innovation, and shaping the future of India Advertising.

You will follow and contribute to the technical direction of our offerings and solutions, working across the India Advertising organization with many different technologies including LLM orchestration, RAG pipelines, and agentic systems.

You will code, troubleshoot, and support high-volume, low-latency distributed systems — including ML model serving and real-time feature stores. What you create is also what you own.

You will participate in implementing key functional areas of the customer experience, including AI-powered advertising products, website applications, and platform services.

You will work with the business team and project managers to convert functional requirements into technical features — leveraging AI to accelerate experimentation and delivery.

You will own operating our products, driving excellence in feature stability, performance, flexibility, and responsible AI practices.