Overview You join a focused, agile team accelerating AI performance across micro-architecture and end-to-end workloads. In this role, you own performance modeling and analysis for current and future AI tasks, translating ideas into simulator implementations and guiding architecture decisions with data. You will run large-scale experiments, explore design spaces, and collaborate with chip, system, and software architects to improve latency, throughput, and efficiency. This position offers impact across silicon, systems, and software, with a mission-driven culture that values growth, collaboration, and inclusion.
Responsibilities- Extend and adapt simulation infrastructure for AI inference micro-architectures
- Analyze latency, throughput, and efficiency for AI inference workloads
- Drive design-space exploration using AI-assisted workflows and large-scale experiments
- Communicate performance insights to influence architecture decisions
- Collaborate with chip, system, and software architects to evaluate variations
Key requirements- Bachelor's Degree in Computer Science or related technical field
- 8+ years of technical engineering experience
- Proficiency in C/C++, Python or equivalent
- clear communication of complex results
- cross-functional collaboration
- data-driven decision making
- performance modeling
- simulation and benchmarking
- AI inference acceleration
