Remote-First Senior AI Inference Hardware Architect

Positron AI

United States

On-site

USD 200,000 - 300,000

Full time

8 days ago

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Benefits offered by this job

Health, dental, vision insurance
Life and disability coverage
Unlimited paid time off
Remote-first culture
Equity

Job summary

Positron AI is seeking a Principal ASIC Architect to define the future of AI inference hardware in the United States. You will collaborate across architecture, software, ML, systems, and silicon implementation to design next-generation accelerators for frontier models.

The role requires breadth across theory and practice, including performance modeling, architectural exploration, and close alignment with workload needs.

Qualifications

  • 15+ years of experience in ASIC architecture.
  • Deep expertise in AI accelerator design and high-performance SoCs.
  • Hands-on experience building performance models for memory systems and interconnects.
  • Strong hardware/software co-design ability.
  • Excellent written and verbal communication skills.

Responsibilities

  • Own architectural exploration across transformer models, MoE, sparse models, and long-context inference.
  • Evaluate techniques including speculative decoding, continuous batching, KV-cache evolution, sub-quadratic and linear attention, and state-space models.
  • Assess memory architectures, communication architectures, and interconnects for next-generation accelerators.
  • Partner with compiler, runtime, system software, firmware, ASIC engineering, and ML research teams to align hardware direction with workloads.

Skills

ASIC architecture
AI accelerator design
Memory/interconnect modeling
Hardware/Software co-design
Excellent communication

Job description

Positron AI is seeking a Principal ASIC Architect to define the future of AI inference hardware in the United States. You will collaborate across architecture, software, ML, systems, and silicon implementation to design next-generation accelerators for frontier models.

The role requires breadth across theory and practice, including performance modeling, architectural exploration, and close alignment with workload needs.

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