ML Network Development Engineer – Infrastructure

Amazon; New York (NY); On-site; USD 156,000 - 211,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Data Services, Inc. is seeking a Network Development Engineer to join the ML-focused Network Fabric Engineering team in New York.

You will build and operate high-availability networks that power ML training and inference workloads, collaborating across software, hardware and security teams to ensure scalable, reliable connectivity. The role emphasizes engineering excellence, automation, and documentation, with on-call responsibilities and opportunities to influence network design across

Qualifications

• Basic Qualifications include 4+ years of major internet routing protocols experience.
• 4+ years of Linux/Unix experience.
• 4+ years of designing large scale networks.
• 4+ years of operating large scale networks and operational excellence.

Responsibilities

• Create and implement changes on the network.
• Work with automation teams to scale tools.
• Lead network projects in deployment, scaling and optimization.
• Provide critical network support to diagnose and resolve large-scale events.
• Troubleshoot routing, interconnectivity, platforms and configurations.
• Create and review documentation and processes regarding deployments.

Skills

Routing protocols

Linux/Unix

Large-scale network design

Network operations

Automation scripting

Machine learning fundamentals

End-to-end network optimization

Job description

Amazon Data Services, Inc. is seeking a Network Development Engineer to join the ML-focused Network Fabric Engineering team in New York.

You will build and operate high-availability networks that power ML training and inference workloads, collaborating across software, hardware and security teams to ensure scalable, reliable connectivity. The role emphasizes engineering excellence, automation, and documentation, with on-call responsibilities and opportunities to influence network design across