Virtual Platform Engineering Sr. Manager, Annapurna Labs Machine Learning Accelerators, AWS
AWS's Trainium and Inferentia chips power the world's largest machine learning clusters. Our team builds virtual platforms — full-system C++ models of these custom SoCs — that let software teams start development months before silicon exists. For Trainium3, our virtual platform enabled a full training workload within 12 hours of first silicon, putting servers in customer hands within weeks!
Responsibilities
- Lead the team delivering virtual platforms used by design verification as well as driver, runtime, collectives, and application software teams to develop and validate software pre‑silicon
- Own the virtual platform roadmap — deciding what to model, at what fidelity, and when to deliver it, based on customer needs and chip schedules
- Drive platform usability, performance, and scalability so teams can run real workloads on your models efficiently
- Build and improve the tooling, CI, and release infrastructure around the virtual platform so customers get reliable, well‑documented drops
- Partner closely with software teams and design verification to understand their workflows and shape the platform to maximize their productivity
- Hire and develop a team of strong modeling engineers, setting high standards for code quality, testing, and delivery
- Dive into technical problems when needed – debug model issues, review architecture decisions, and unblock the team
Why this role is interesting
- Your virtual platform directly accelerates AWS's most strategic silicon programs — software teams literally can't start without you
- You'll own a product with real internal customers who give you direct feedback, not just a component buried in a larger system
- The problem space is rich: full-system simulation, multi-subsystem integration, QEMU development, performance at scale, machine learning at the bleeding edge
- Small team, big impact, startup pace inside AWS's custom silicon org
Machine Learning (ML) background not required. You'll learn the necessary ML domain knowledge on the job. What matters is deep virtual platform or system modeling experience and the ability to lead a technical team.
About the Team
- More details about Trainium3, our team's latest achievement, as well as some insights into our team culture (link removed)
Basic Qualifications
- 7+ years of engineering team management experience
- Knowledge of SoC architecture
- 15+ years writing functional or performance models for SoCs, CPUs, GPUs, or ASICs
- Strong C++ and/or SystemC skills in large-scale OOP codebases
Preferred Qualifications
- Experience hiring, developing and promoting engineering talent
- Experience with high-performance, multi-threaded, or distributed systems
- Experience developing and calibrating performance models for custom silicon
- Background writing benchmarks and analyzing model performance
- ML accelerator architecture knowledge (a plus, not required)
- Experience building CI/CD regression frameworks and developer tooling
- Familiarity with AWS EC2 for development workflows
Benefits and Compensation
Base salary range: USD $253,100.00 – $342,300.00 annually. Your Amazon package will include sign‑on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits: 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, and parental leave. Learn more about our benefits at
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Location: United States, CA, Cupertino.