Senior Machine Learning Engineer

15 hours ago


Santa Clara, California, United States Amazon Full time

Amazon - An Industry Leader in E-commerce and Technology

We are seeking talented Senior Machine Learning Engineers to join our team at Amazon, working on various AI projects that enhance the shopping experience for our customers. As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying large-scale machine learning models that improve product recommendations, search results, and other core features of our platform.

About the Role:
  • Develop innovative solutions using deep learning and natural language processing techniques to drive business growth and customer satisfaction.
  • Collaborate with cross-functional teams, including software development, data science, and product management, to integrate ML models into our products.
  • Design and implement scalable and efficient algorithms and data pipelines to process large datasets.
  • Work closely with technical leaders to define and deliver strategic initiatives that drive business impact.
  • Stay up-to-date with the latest advancements in machine learning and AI, applying new techniques and tools to drive innovation.
What We Are Looking For:
  • 3+ years of experience building models for business applications, or Ph.D. or Master's degree with equivalent industry experience.
  • Experience with languages like Java, C++, Python, and related technologies.
  • Strong background in algorithms, data structures, and software development.
  • Experience with cloud-based services like AWS, GCP, or Azure.
  • Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams.
Compensation and Benefits:

$200,000 - $300,000 per year, depending on experience and qualifications.

As a leading company in e-commerce and technology, we offer a competitive compensation package, comprehensive benefits, and opportunities for career growth and professional development.

Please note that these figures are estimates based on national averages and may vary based on location and individual circumstances.



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