Embedded Networking Engineer – Nitro SDN for ML

Amazon; Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon Development Center U.S., Inc. is seeking an Embedded Software Engineer for EC2 Nitro Networking to own design, implementation, and testing of dataplane performance optimizations powering ML workloads and cloud networking at scale.

The role involves collaborating with senior engineers across EC2, AWS, and Amazon, mentoring juniors, and delivering robust, scalable solutions for diverse cloud applications.

Qualifications

• Bachelor's degree in computer science or equivalent.
• 4+ years of non-internship professional software development experience.
• 4+ years of programming with at least one software programming language experience.
• 3+ years of contributing to systems architecture and design (architecture, design patterns, reliability and scaling).
• 4+ years of full software development life cycle, including coding standards, code reviews, source control, build processes, testing and operations.

Responsibilities

• Design, scoping, implementation, and integration testing of performance optimizations and dataplane features for the EC2 Nitro System.
• Set high standards for development processes, tools, and automation.
• Influence best engineering practices on design and coding.
• Identify business problems and advocate for technical solutions influencing the team roadmap.
• Mentor junior engineers in scoping, design, and scalable code development.
• Collaborate with Senior/Principal Engineers and cross-functional teams to define requirements and architectures.

Skills

C/C++

Embedded development

System performance

Memory management

Parallel computing

Education

Bachelor's degree in CS

Job description

Amazon Development Center U.S., Inc. is seeking an Embedded Software Engineer for EC2 Nitro Networking to own design, implementation, and testing of dataplane performance optimizations powering ML workloads and cloud networking at scale.

The role involves collaborating with senior engineers across EC2, AWS, and Amazon, mentoring juniors, and delivering robust, scalable solutions for diverse cloud applications.