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1 месяц назад

Architecture Modeling Engineer (AI Accelerator)

Формат работы
remote (Global)/onsite
Тип работы
fulltime
Грейд
senior
Английский
b2
Страна
France/US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

Текст:
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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

hirify.global 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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