Senior Applied Scientist, Amazon Core Search

As an Applied Scientist on the team, you will lead science innovation to improve the customer search experience through higher-quality autocomplete search results. You will: - Develop and deploy ML models to produce high-quality, diverse search autocomplete suggestions. - Design and train semantic matching models (bi-encoders, cross-encoders, and distillation from large foundation models) for suggestion ranking and relevance. - Develop reinforcement learning and reward-modeling approaches to continuously improve suggestion quality. - Train multi-objective ranking and scoring systems that balance suggestion diversity, specificity, and relevance. - Design and implement scalable model architectures optimized for strict latency constraints, including knowledge distillation, quantization, and efficient inference strategies for production deployment. - Lead end-to-end science projects from problem formulation through production launch, mentoring scientists and collaborating closely with engineers and scientists within and outside the team to deliver customer-facing impact. BASIC QUALIFICATIONS - PhD, or Master's degree - 6+ years of building machine learning models or developing algorithms for business application experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with large scale distributed systems such as Hadoop, Spark etc.

Amazon is a global technology company operating in e-commerce, cloud computing (AWS), digital streaming, advertising and artificial intelligence. Its India operations span development centres in Bengaluru, Hyderabad, Chennai, Pune, Gurugram and Mumbai, covering retail technology, AWS infrastructure, Alexa, advertising, payments and supply-chain systems.