C/C++ HW/SW Co-Design SDE for ML Acceleration

Amazon Inc.; Cupertino (CA); On-site; USD 165,000 - 224,000; Full time

Job summary

Annapurna Labs is hiring a C/C++ Hardware / Software Co-Design SDE to develop bare metal firmware for neural network model execution on custom ASIC ML accelerators. You will work at the hardware/software intersection, co-design firmware with RTL, and collaborate with design teams to accelerate AI workloads.

The role emphasizes building high-performance, scalable systems, with opportunities to shape ML hardware and software from pre- to post-silicon development within the AWS ecosystem.

Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• 2+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience.
• 3+ 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
• Experience in computer architecture
• Experience writing firmware or bare metal software using C/C++

Responsibilities

• Software / hardware architecture and co-design
• Bare metal C/C++ software development, testing, debug, and performance improvements
• Test suite and infrastructure development
• Developing software which can be maintained, improved upon, documented, tested, and reused
• Close collaboration with RTL designers, design verification engineers, other software teams and customers

Skills

C/C++

Java

C#

Education

Bachelor's degree in computer science

Job description

Annapurna Labs is hiring a C/C++ Hardware / Software Co-Design SDE to develop bare metal firmware for neural network model execution on custom ASIC ML accelerators. You will work at the hardware/software intersection, co-design firmware with RTL, and collaborate with design teams to accelerate AI workloads.

The role emphasizes building high-performance, scalable systems, with opportunities to shape ML hardware and software from pre- to post-silicon development within the AWS ecosystem.