Machine Learning Engineer for Personalization Systems

hace 4 días


Madrid, Madrid, España Amazon A tiempo completo

Company Overview: Amazon is a leader in e-commerce and cloud computing, providing a wide range of products and services to millions of customers worldwide. Our Prime membership program offers unparalleled convenience, speed, and selection, making it an essential part of many people's lives.

Job Summary

We are seeking a highly skilled Machine Learning Engineer to join our team of scientists and engineers developing algorithms to personalize the customer experience with Amazon Prime. As a key member of our team, you will design, develop, and deploy machine learning models that drive business impact by adapting to individual customer preferences and behaviors.

Key Responsibilities:

  • Build and develop machine learning models at scale, leveraging AWS technologies such as EMR, Spark, Redshift, Sagemaker, DynamoDB, and S3.
  • Leverage techniques from supervised learning, multi-armed bandits, optimization, and reinforcement learning to create contextual recommendation systems.
  • Analyze and extract relevant information from large amounts of Amazon's historical business data to automate and optimize key processes.
  • Collaborate closely with software engineering teams to integrate machine learning models into production environments.
  • Develop offline policy estimation tools and integrate them with reporting systems to measure model performance.
  • Design, develop, and evaluate innovative models and statistical approaches to understand and predict customer behavior.

Requirements:

  • Bachelor's degree in Computer Science, Engineering, or related field.
  • Proven experience in machine learning, data mining, and statistical modeling.
  • Strong programming skills in languages such as Python, Java, or C++.
  • Experience with cloud-based technologies such as AWS.
  • Excellent communication and collaboration skills.

Estimated Salary: $180,000 - $250,000 per year, depending on experience and location.



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