[Remote] Senior Virtual Platform Software Engineer, Annapurna Labs Machine Learning Accelerators, AWS
Note: The job is a remote job and is open to candidates in USA. Amazon Web Services (AWS) is seeking a Senior Virtual Platform Software Engineer for its Annapurna Labs Machine Learning Accelerators team. In this role, you will build and own functional models of SoC subsystems for virtual platforms, enabling software teams to start development ahead of silicon availability while improving simulation performance and usability.
Responsibilities
- 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
- 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
Skills
- 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
- 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
Benefits
- Sign-on payments
- Restricted stock units (RSUs)
- Comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
- 401(k) matching
- Paid time off
- Parental leave
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