Senior ML Systems Engineer, EC2 Nitro

Amazon Inc.; Seattle (WA); On-site; USD 168,000 - 227,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance

401(k) matching

Job summary

Amazon.com Services LLC is seeking a Senior Software Development Engineer for the EC2 Nitro ML platforms. You will drive development across hardware, firmware, and software stacks, focusing on scalable ML workloads.

The role requires strong CS fundamentals and expertise in C/C++ or Rust on Linux, including build systems, version control, and unit testing. Leadership and collaboration with cross-functional teams are essential.

Qualifications

• 5+ years of non-internship professional software development experience.
• 5+ years of programming with at least one software programming language experience.
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• Experience as a mentor, tech lead or leading an engineering team.
• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience.
• Bachelor's degree in computer science or equivalent.

Responsibilities

• Drive development for new EC2 machine learning platforms across hardware, firmware, systems and application software.
• Collaborate with broad technical teams to implement scalable, reliable ML-focused solutions.
• Provide mentorship and leadership to engineering teams and review architectures and designs.
• Contribute to design patterns, reliability, and performance improvements across EC2 Nitro and MLS initiatives.

Skills

C/C++

Rust

Linux

Mentor/Tech lead

Leadership

Education

Bachelor's degree in computer science or equivalent

Tools

Linux package management

Version control

Build automation

Unit testing

Job description

Amazon.com Services LLC is seeking a Senior Software Development Engineer for the EC2 Nitro ML platforms. You will drive development across hardware, firmware, and software stacks, focusing on scalable ML workloads.

The role requires strong CS fundamentals and expertise in C/C++ or Rust on Linux, including build systems, version control, and unit testing. Leadership and collaboration with cross-functional teams are essential.