Software Dev Engineer

Teamblind, Inc.; Toronto; On-site; CAD 110,000 - 170,000; Full time

Job summary

Amazon is seeking a Software Engineer to collaborate with hardware, firmware, compiler, runtime, and ML teams to develop software for custom ML accelerator silicon. You will design, develop, and test software across the accelerator stack, including toolchains, drivers, runtimes, profiling, and validation infrastructure.

You will build scalable systems, write high-quality code in C/C++/Python/Rust, and contribute to CI/CD pipelines and tooling.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related STEM field.
• Demonstrated experience with systems-level and performance-critical development is preferred.

Responsibilities

• Collaborate with hardware design, firmware, compiler, runtime, and ML engineers to develop software for custom ML accelerator silicon.
• Design, develop, and test software across the accelerator stack, including compiler toolchains, device drivers, runtime libraries, profiling tools, simulation frameworks, or chip validation infrastructure.
• Build scalable, high-performance systems supporting chip verification, silicon bring-up, or production ML inference/training workloads.
• Write clean, maintainable code (C, C++, Python, or Rust) following best practices for systems-level and performance-critical development.
• Develop CI/CD pipelines, test automation, and tooling to accelerate the hardware-software co-development lifecycle.
• Participate in code reviews, contribute to technical documentation, and leverage GenAI tools to enhance development productivity.
• Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities.
• Stay current with emerging technologies in ML accelerators, compiler optimization, computer architecture, and cloud-scale distributed systems.

Skills

C

C++

Python

Rust

Education

Bachelor's degree in Computer Science or related STEM field

Job description

Key job responsibilities

• Collaborate with cross-disciplinary teams that may include hardware design, firmware, compiler, runtime, and ML engineers to develop software that enables and optimizes custom ML accelerator silicon
• Design, develop, and test software across the accelerator stack, including compiler toolchains, device drivers, runtime libraries, profiling tools, simulation frameworks, or chip validation infrastructure
• Build scalable, high-performance systems supporting chip verification, silicon bring-up, or production ML inference/training workloads
• Write clean, maintainable code (C, C++, Python, or Rust) following best practices for systems-level and performance-critical development
• Develop CI/CD pipelines, test automation, and tooling to accelerate the hardware-software co-development lifecycle
• Participate in code reviews, contribute to technical documentation, and leverage GenAI tools to enhance development productivity
• Demonstrate operational excellence through monitoring, debugging, and resolving issues across hardware-software integration boundaries, including on-call responsibilities
• Stay current with emerging technologies in ML accelerators, compiler optimization, computer architecture, and cloud-scale distributed systems

A day in the life

As an Amazonian, you will be matched to a manager and a team, and will have the opportunity to influence the evolution of Amazon technology and work on critical projects early in your career. In addition to working on impactful projects, you will have the opportunity to engage with Amazonians for both personal and professional development, expand your network, and participate in various activities. We give you the tools to own your projects and learn in a real-world settings.

BASIC QUALIFICATIONS

• Currently has, or is in the process of obtaining a Bachelor's degree or above in Computer Science, Computer Engineering, Electrical Engineering, or related STEM field
• Demonstrated experienc