2 дня назад
Principal Architect - Performance Analysis and Modeling
195 000 - 285 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Principal Architect - Performance Analysis and Modeling (AI Accelerators): Analyzing multimodal LLM, reasoning, and video/audio-generation workloads and creating analytical models to project performance for current and future inference accelerators, with an accent on computer architecture, hardware-software codesign, and emerging memory and interconnect technologies. Focus on identifying functional and performance implications of machine learning algorithms, building architecture simulators and performance models, and proposing hardware and software features for datacenter inference.
Location: Hybrid in Santa Clara, California, with onsite work at the headquarters 3 days per week
Salary: $195,000–$285,000 per year, plus equity and bonus opportunities
Company
develops hardware and software technologies for generative AI and datacenter inference acceleration.
What you will do
- Analyze emerging machine learning workloads, including multimodal LLMs, chain-of-thought reasoning models, and video/audio generation.
- Contribute hardware and software features for next-generation inference accelerators.
- Analyze emerging machine learning algorithms and workloads to identify functional and performance implications.
- Create analytical models and architecture simulators to project performance across current and future hardware generations.
- Propose hardware and software features that enable or accelerate new algorithms.
- Collaborate with Product, Hardware Design, Compiler, Inference Server, and Kernel teams while tracking current research in ML architecture and algorithms.
Requirements
- Bachelor's degree in Electrical Engineering with 10+ years of industry experience, or a preferred master's degree with 8+ years of industry experience.
- Academic or industry experience in multiple relevant areas, including computer architecture, hardware-software codesign, performance modeling, and machine learning fundamentals, particularly deep neural networks.
- Programming fluency in C, C++, or Python.
- Experience developing analytical performance models and architecture simulators for performance analysis.
- Self-motivation, collaboration skills, and initiative.
Nice to have
- Research background with publications in top-tier computer architecture or machine learning venues such as ISCA, MICRO, ASPLOS, HPCA, DAC, or MLSys.
Culture & Benefits
- Collaborative and inclusive environment focused on respect, humility, direct communication, and execution.
- Medical, dental, and vision coverage.
- 401(k) and an employee rewards plan supporting employee and family wellbeing.
- Individual and company performance-based incentive opportunities.
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