Software Development Manager, Worldwide Returns & Recommerce

Amazon Amazon · Big Tech · Bellevue, WA · Software Development

This role is for a Software Development Manager on the Worldwide Returns & ReCommerce team at Amazon. The team builds AI and machine learning infrastructure for global reverse logistics, focusing on automating decision-making, maximizing financial recovery, and optimizing processing efficiency. The manager will lead teams in developing and deploying NLP, Computer Vision, and Classical ML models, as well as the associated infrastructure for model hosting, grading pipelines, and low-latency inference.

What you'd actually do

  1. 3+ years managing software development or machine learning engineering teams, including hiring, mentoring, and developing technical talent
  2. 4+ years architecting large-scale model hosting infrastructure, low-latency inference runtimes, and end-to-end model management workflows
  3. 2+ years of hands-on programming experience in Java, C++, Python, or related languages, with a focus on writing highly optimized, production-ready code
  4. Proficiency in Natural Language Processing (NLP), Computer Vision (CV), and core machine learning (ML) engineering design patterns.
  5. Proven experience in Operational Excellence (DevOps/MLOps), Data Engineering/Pipelines, and Cross-Functional Leadership (collaboration with Applied Science and Product teams).

Skills

Required

  • Software development team management
  • Machine learning engineering team management
  • Hiring, mentoring, and developing technical talent
  • Architecting large-scale model hosting infrastructure
  • Low-latency inference runtimes
  • End-to-end model management workflows
  • Java
  • C++
  • Python
  • Highly optimized, production-ready code
  • Natural Language Processing (NLP)
  • Computer Vision (CV)
  • Core machine learning (ML) engineering design patterns
  • Operational Excellence (DevOps/MLOps)
  • Data Engineering/Pipelines
  • Cross-Functional Leadership
  • Collaboration with Applied Science and Product teams
  • Communication skills

Nice to have

  • Communicating complex system architectures, MLOps strategies, and AI solutions to all levels of the organization
  • Recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers

What the JD emphasized

  • architecting large-scale model hosting infrastructure, low-latency inference runtimes, and end-to-end model management workflows
  • writing highly optimized, production-ready code
  • Operational Excellence (DevOps/MLOps)
  • Data Engineering/Pipelines
  • NLP
  • CV
  • ML engineering design patterns

Other signals

  • building the AI and machine learning infrastructure that powers Amazon’s global reverse logistics
  • deploy NLP, Computer Vision (CV), and Classical ML to solve high-stakes engineering and asset-optimization challenges at scale
  • engineering production AI/ML platforms that automate decision-making, maximize financial recovery, and optimize processing efficiency
  • design the high-throughput model hosting infrastructure, intelligent grading pipelines, and low-latency inference runtimes