Develop backend code generation capabilities across heterogeneous platforms
Profile, analyze and optimize system level performance, develop new tooling where necessary
Participate in design reviews, API development, and documentation
Successfully collaborate with hardware, software, applied science and product teams to onboard more and more user experiences to be powered by Deep Learning accelerator.
Mentor and provide guidance to junior engineers
A day in the life
You join a small team building the compiler that brings large AI models to a new generation of custom silicon. The chip has a fraction of the memory of a phone, and the compiler is what makes language models run on it at all. The team is small enough that each engineer owns a meaningful piece of the system end to end. There is no layer between you and the problem.
The morning starts with results from an overnight run. A piece of the compiler you own just produced its tightest result yet on a real model. You ship the change for hardware validation.
You spend the afternoon directing AI agents through the codebase, reviewing their changes, and steering the design.
Before lunch, you load your compiled model onto the chip and run it through a demo app you wrote yourself, watching tokens stream out of silicon you helped make work. Later, you meet with the research team. They depend on your component. You sketch a cleaner interface together.
About the team
We sit at the intersection of AI models and custom silicon, and our work decides what is possible at the edge.
Engineers here bring deep experience across compilers and program analysis, optimization algorithms, computer architecture, machine learning systems, and the practical craft of getting large software to run reliably under tight constraints. People have shipped production code generators, tuned schedulers for novel hardware, and worked at every layer from the model down to the bare metal.
Because the team is small, you work alongside that experience daily, not at a distance. You partner directly with researchers shaping the models, hardware engineers shaping the silicon, and firmware engineers shaping the runtime. You learn how each layer constrains and unlocks the others, and you see your decisions land end to end.
This is a place to build technical depth quickly and own work that matters from day one.
2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
3+ years of non-internship professional software development experience
3+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware
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 embedded development in C/C++
Knowledge of system performance, memory management, and parallel computing principles
Experience building compiler for application specific accelerators or custom instruction set
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, BC, Vancouver - 114,800.00 - 191,800.00 CAD annually
