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Tier-1 brand and metro location increase density, but specialized ML research requirements reduce generalist applicant competition.
Role requires ML research, LLM and recommender expertise making backgrounds less transferable.
Research publications, deep-learning expertise, and production ML engineering imply strict technical filters.
Lead research and experimentation in machine learning solutions focused on Competitive Monitoring systems, including large language models and recommender systems.
Collaborate with engineers to develop, deploy, and maintain state-of-the-art ML models impacting global customer experience.
Contribute to the scientific roadmap of the CMT team and engage in cross-functional knowledge sharing through technical writing and presentations.
Proficient in programming with Java, C++, Python, or related languages.
Experience with SQL and RDBMS or Data Warehouses such as Oracle.
Demonstrated experience building machine learning models or algorithms for business applications, including expertise in deep learning model architecture, training, optimization, and pruning.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced applied scientist comfortable experimenting with and implementing state-of-the-art deep learning architectures and optimization strategies.
Capable of end-to-end ML solution delivery, working collaboratively with engineers to deploy production-ready systems.
Evidence of research aptitude demonstrated by publications in top-tier peer-reviewed conferences or journals is preferred but not mandatory.