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Strong Tier-1 brand, metro location, and mid-level generalist ML role drive high competition.
Core ML/NLP skills transfer across industries, but search-specific production experience raises sensitivity.
Requires 3+ years, advanced degree, publications/patents, and production ML skills, so strict shortlisting.
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Lead the development, deployment, and continuous improvement of ML models for Amazon Search relevance, including query understanding, semantic matching, and ranking.
Design and implement scalable, low-latency model architectures using methods like knowledge distillation and quantization for production deployment across multiple languages and locales.
Manage end-to-end science projects from problem formulation to production launch collaborating with cross-functional teams to enhance customer search experience.
3+ years of experience building machine learning models for business applications.
PhD or Master's degree in a relevant field.
Proficiency in programming with Java, C++, Python, or related languages.
Experience in algorithms and data structures, parsing, numerical optimization, data mining, distributed or high-performance computing.
Experienced applied scientist with strong background in NLP, ML, and deep learning applied to search relevance and ranking problems.
Capable of leading full lifecycle projects including model design, training, optimization, and scalable production deployment under latency constraints.
Able to work effectively cross-functionally with engineers and scientists to deliver measurable improvements in customer-facing search products.