Accelerator Software Engineer - Chip-to-Host Inference

The Consensus; San Jose (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Medical, dental, and vision coverage

$500 monthly credit to waive medical

Housing subsidy for office proximity

Relocation support to San Jose

Wellness benefits

Daily lunch and dinner in office

Unlimited compute budget

Job summary

Etched in San Jose seeks an engineer to own the accelerator software that makes our chips usable. You’ll work across ASIC firmware, platform software for power sequencing and bring-up, and host-side kernel drivers to expose the device to the inference stack.

You’ll specialize in one area while contributing across others as the team grows, collaborating with hardware and software groups to ship production-ready software and drive reliability in a cutting-edge frontier AI system.

Qualifications

• Bachelor's degree or equivalent practical experience.
• Strong software development fundamentals, including data structures and algorithms.
• Experience shipping and testing software on products that have gone to production.
• Depth in firmware design, implementation, and debugging.
• Familiarity with embedded architectures and IO technologies at silicon-to-host boundary.

Responsibilities

• Own accelerator software spanning ASIC firmware, microcontroller firmware, and host kernel interfaces.
• Collaborate across ASIC, platform, and host software to bring chip to life.
• Work across three domains: ASIC firmware, microcontroller firmware, and host-side kernel and drivers.

Skills

Strong software fundamentals

Data structures & algorithms

Production software experience

Firmware design & debugging

Embedded architectures familiarity

Education

Bachelor's degree or equivalent practical experience

Job description

Etched in San Jose seeks an engineer to own the accelerator software that makes our chips usable. You’ll work across ASIC firmware, platform software for power sequencing and bring-up, and host-side kernel drivers to expose the device to the inference stack.

You’ll specialize in one area while contributing across others as the team grows, collaborating with hardware and software groups to ship production-ready software and drive reliability in a cutting-edge frontier AI system.