1 месяц назад
Architecture Modeling Engineer (AI Accelerator)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Architecture Modeling Engineer (AI Accelerator): Developing performance models and workload-analysis tools for an optical AI accelerator with an accent on computer architecture, AI workloads, and hardware-software co-design. Focus on evaluating compute, memory, interconnect, and scheduling trade-offs, defining workload mapping, and optimizing kernels for target silicon.
Location: Paris offices or remote from North America. The listing also specifies an on-site location type for the Paris office option.
Company
develops proprietary processors that fuse optical and CMOS technologies to improve AI computing performance.
What you will do
- Develop performance models to evaluate optical AI accelerator architecture choices and guide early design decisions.
- Analyze AI workloads, kernels, dataflows, and system bottlenecks with the software team.
- Model compute, memory, interconnect, and scheduling behavior with hardware architects.
- Lead performance studies and trade-off analyses across throughput, latency, utilization, bandwidth, and efficiency.
- Help define and validate the accelerator programming model and workload-mapping strategy.
- Optimize compute kernels and build simulation, profiling, and analysis tools for architecture exploration and software optimization.
Requirements
- Strong mathematical background in linear algebra, probability, numerical methods, and quantitative performance analysis.
- Strong knowledge of computer architecture, including compute pipelines, memory hierarchies, interconnects, and parallel execution.
- Strong C, C++, and Python programming skills.
- Experience analyzing and optimizing performance-critical kernels or low-level compute workloads.
- Good understanding of AI/ML workloads, tensor operations, data movement, and common execution patterns.
- Proficient English is required.
Nice to have
- Industry knowledge of AI hardware, GPUs, memory generations, and rack-scale computing.
- Experience building performance models, simulators, or analytical models for CPUs, GPUs, NPUs, or other accelerators.
- Experience with profiling, benchmarking, and identifying hardware or software performance bottlenecks.
- Experience with analog computing, in-memory computing, or heterogeneous systems.
Culture & Benefits
- Competitive cash compensation based on location, experience, and internal team pay levels.
- Meaningful stock option plan included in the majority of full-time offers.
- Healthcare coverage, including family-friendly options, and pension contributions.
- Professional development support and 25 days of paid time off in addition to public holidays.
- Ownership of a key technical domain with opportunities for vertical and horizontal growth.
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