Principal Applied Scientist, Machine Learning Expert

3 days ago


Seattle, Washington, United States Amazon Full time
About the Role

We are seeking a highly skilled Principal Applied Scientist to join our Machine Learning team at Amazon. As a key member of our team, you will be responsible for developing and implementing cutting-edge machine learning algorithms and models to drive business growth and improve customer experience.

Key Responsibilities
  • Design and develop large-scale machine learning systems to optimize business outcomes
  • Collaborate with cross-functional teams to integrate machine learning solutions into our products and services
  • Develop and maintain high-quality machine learning models and algorithms
  • Conduct thorough analysis and evaluation of machine learning results to inform business decisions
  • Stay up-to-date with the latest advancements in machine learning and AI research
Requirements
  • PhD degree in Computer Science, Machine Learning, Engineering, Statistics, or a related field
  • 8+ years of hands-on experience developing and implementing machine learning algorithms and models
  • Strong demonstrated skills in implementing and deploying large-scale machine learning applications and tools
  • Excellent communication and data presentation skills
  • Strong problem-solving ability
Preferred Qualifications
  • Experience in deep learning algorithms and systems
  • Experience in generative AI and Large Language Models (LLMs) applications
  • Programming experience in Java, C, C++, or Python
  • Experience using statistical software packages such as R or Python
  • Experience with Amazon Web Services and cloud computing technologies
  • Experience with distributed systems for processing large data
About Amazon

Amazon is a customer-obsessed company that is committed to innovation and excellence. We are a total compensation company, offering a comprehensive benefits package, including medical, financial, and other benefits. Our compensation reflects the cost of labor across several US geographic markets, and pay is based on a number of factors, including market location and job-related knowledge, skills, and experience.



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