Software Engineer - ML‑Driven Discovery & Scale

Amazon

Seattle (WA)

On-site

USD 144,000 - 194,000

Full time

14 days+

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Job summary

Amazon in Seattle is seeking a Software Development Engineer to help customers discover across categories and build scalable, customer-centric features using machine learning and AWS services.

You will contribute to design, development, testing, and operations, delivering robust back-end services and intuitive interfaces while collaborating in an agile environment.

This role emphasizes GenAI exploration and high-quality software practices.

Qualifications

  • 3+ years of non-internship professional software development experience.
  • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience programming with at least one software programming language
  • Bachelor's degree or equivalent

Responsibilities

  • Work with the team to drive business decisions
  • Design, implement, test, deploy and maintain innovative software solutions to transform service performance, compliance, durability, cost, and security.
  • Use software engineering best practices to ensure a high standard of quality for all of the team deliverables
  • Leverage GenAI in science for model building and in software development
  • Write high quality distributed system software
  • Work in an agile development environment, where you prioritize the highest value solutions for customers.

Skills

Software development
System design
Programming

Education

Bachelor's degree or equivalent

Job description

Amazon in Seattle is seeking a Software Development Engineer to help customers discover across categories and build scalable, customer-centric features using machine learning and AWS services.

You will contribute to design, development, testing, and operations, delivering robust back-end services and intuitive interfaces while collaborating in an agile environment.

This role emphasizes GenAI exploration and high-quality software practices.

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