Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWS

About the role

AWS's Trainium and Inferentia chips power the world's largest machine learning clusters. Our team builds virtual platforms — full-system C++ and SystemC models of these custom SoCs — that let software teams start development months before silicon arrives. For Trainium3, our virtual platform enabled running a full training workload within 12 hours of first silicon. We're looking for a software engineer to build and own the models and infrastructure that make this possible.

What you'll do:

- Build and own functional models of SoC subsystems that integrate into our full-system virtual platform, used by firmware, driver, runtime, and application software teams

- Develop and improve the virtual platform infrastructure: QEMU integration, simulation performance, build and release tooling, and customer-facing documentation

- Design models for usability and performance — your customers are software engineers who need to run real workloads on your platform efficiently

- Develop and improve the virtual platform infrastructure: QEMU integration, simulation performance, build and release tooling, and customer-facing documentation

- Work with software teams (your primary customers) to understand their workflows, debug issues on the platform, and shape the model to maximize their productivity

- Drive simulation performance improvements so the platform can handle increasingly complex workloads at scale

- Contribute to model architecture decisions — choosing the right level of abstraction and fidelity for each subsystem based on customer needs

Why this role is interesting:

- You'll own a product that software teams across AWS depend on — they literally can't start development without your virtual platform

- The engineering challenges are genuinely interesting: full-system simulation, multi-subsystem integration, QEMU development, performance optimization at scale

- You'll see the direct impact of your work when software teams hit the ground running on new silicon

- As the team grows, there's a path into architectural modeling — using the platform to explore design alternatives and influence chip architecture

- Small team, startup pace, big impact inside AWS's custom silicon org

You will thrive in this role if you:

- Have built functional models, virtual platforms, or system-level simulations for SoCs, ASICs, GPUs, or CPUs

- Think of yourself as a software engineer first, with deep domain knowledge in chip architecture

- Are comfortable in C++ or SystemC, and familiar with Python for tooling

- Care about your customers' experience — you think about usability, documentation, and reliability, not just model accuracy

- Are interested in expanding into performance or architectural modeling as the team scales

- Enjoy working on a small, high-impact team where you own significant pieces of the stack