Applied Scientist Machine Learning Hiring
Amazon Science
Advance hiring science at Amazon through machine learning, artificial intelligence, and natural language processing research in Vancouver, British Columbia.As an Applied Scientist with Global Hiring Science, you will develop production machine learning solutions that enhance recruitment. You will work with Research Scientists and Software Engineers on fair, accurate hiring models. The work includes modern LLM and GenAI technologies, Amazon’s in-house technology stack, and scientific communication.Key Responsibilities:
Design advanced artificial intelligence models for fair hiring decisionsImplement natural language processing models across diverse data sourcesCollaborate with Research Scientists and Software EngineersPresent ideas clearly and respond effectively to feedbackExplore new techniques in NLP, LLMs, and GenAIRequirements:
Three or more years building models for business applicationsProgramming experience in Java, C++, Python, or related languagesExperience with algorithms and data structuresExperience with data mining or numerical optimizationMaster’s degree in a related field preferredApply machine learning, artificial intelligence, and natural language processing to Amazon’s global hiring science products.
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Design advanced artificial intelligence models for fair hiring decisionsImplement natural language processing models across diverse data sourcesCollaborate with Research Scientists and Software EngineersPresent ideas clearly and respond effectively to feedbackExplore new techniques in NLP, LLMs, and GenAIRequirements:
Three or more years building models for business applicationsProgramming experience in Java, C++, Python, or related languagesExperience with algorithms and data structuresExperience with data mining or numerical optimizationMaster’s degree in a related field preferredApply machine learning, artificial intelligence, and natural language processing to Amazon’s global hiring science products.
#J-18808-Ljbffr
Vacancy posted 5 hours ago
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