Fulfillment Optimization Engineer

hace 2 días


Madrid, Madrid, España Amazon A tiempo completo

About Amazon

Amazon is a global leader in e-commerce and cloud computing, shipping millions of packages to customers worldwide every hour. Our Fulfillment Optimization team plays a critical role in ensuring the efficient delivery of these packages.

Job Summary

We are seeking a highly skilled Fulfillment Optimization Engineer - Big Data Specialist to join our team. As a key member of this team, you will be responsible for designing and building innovative technologies that optimize fulfillment processes using big data processing, scalable micro-service architecture, linear optimization techniques, machine learning, and AI.

Main Responsibilities

  • Collaborate with cross-functional teams to conceive, design, and bring innovative products and services to market.
  • Design and build scalable systems leveraging state-of-the-art technologies to solve complex problems in fulfillment supply chain optimization.
  • Develop solutions to run predictions on distributed systems, exposing individuals to innovative technologies at incredible scale and speed.
  • Build distributed storage, index, and query systems that are scalable, fault-tolerant, low cost, and easy to manage/use.
  • Design and code solutions starting with broadly defined problems, working in an agile environment to deliver high-quality software.

About You

We are looking for individuals who are passionate about creating new products, features, and services from scratch while managing ambiguity and the pace of a company where development cycles are measured in weeks, not years. You should have a strong background in big data processing, scalable micro-service architecture, linear optimization techniques, machine learning, and AI, with experience in designing and building innovative technologies to solve complex problems. The estimated salary for this role is $175,000 - $225,000 per year, based on your qualifications and location within the United States.



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