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

- **Company:** Amazon.com, Inc.
- **Location:** Austin, TX, United States
- **Experience:** Expert
- **Salary:** $193,300.0 - $261,500.0
- **Contract:** Internship / Graduate position
- **Skills:** 3d Models, Amazon Web Services, Data Analysis, Software Applications, C++ (Programming Language), Code Review, Computer Programming, Microarchitecture, Software Debugging, Microprocessors, Firmware, Python (Programming Language), Machine Learning, Performance Tuning, Quick EMUlator (QEMU), Release Management, Software Engineering, SystemC, System Software, Multithreading, Graphics Processing Unit (GPU), Application Specific Integrated Circuits, Pytest, Information Technology, Modeling and Simulation, Build Process, Software Coding, Software Version Control
- **Published:** October 27, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/28133176/Senior-Virtual-Platform-Software-Engineer-Annapurna-Labs-Machine-Learning-Accelerators-Aws-Texas-Austin-7375

## About the Role

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

No ML background needed. You'll learn the ML accelerator domain on the job., 5+ years of non-internship professional software development experience

 - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
 - Experience as a mentor, tech lead or leading an engineering team
 - 7+ years of non-internship professional experience writing functional or performance models
 - Experience programming with C++ and/or SystemC
 - Knowledge of SoC, CPU, GPU, and/or ASIC architecture and micro-architecture

Preferred Qualifications

 - Bachelor's degree in computer science or equivalent
 - Experience analyzing data and applying best practices to assess performance drivers
 - Experience developing models that integrate with QEMU
 - Experience developing and calibrating performance models for custom silicon chips
 - Experience with PyTest and GoogleTest
 - Familiarity with modern C++ (11, 14, etc.)
 - Experience in multi-threaded programming
 - Experience with machine learning accelerator hardware and/or software

## Description

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