Research Hardware Engineer, Neurotech Platform

Convergent Research; San Francisco (CA); On-site; USD 183,000 - 240,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with match

Life and AD&D insurance

Paid holidays

Paid time off

Job summary

Arbor Neuroscience, a nonprofit research organization within the Convergent Research family, is hiring to ensure hardware exists to enable science. The role focuses on mechanical, electrical, and bioengineering across a portable, home-friendly platform, including implants, boards, and benchtop testing, collaborating with an external engineering partner.

You’ll translate scientists' needs into hardware specs, define next-version requirements, and plan in-house vs contracted work.

Qualifications

• Depth in mechanical, electrical, or bioengineering and knowledge of the others to coordinate work
• Experience building functional hardware for research or instrumentation
• Ability to work with external engineering teams and ensure outcomes meet requirements
• Familiarity with CAD and basic board design

Responsibilities

• Translate scientists' needs into hardware requirements
• Own the Forest 1 development and coordinate with an engineering partner
• Design and validate hardware for a platform combining electrophysiology and ultrasound in animals
• Make Forest 1 portable and robust for non-clinical use
• Identify what to build in-house vs contract out and manage contractors
• Prepare platforms for external use with robust documentation and reproducibility

Skills

Mechanical engineering

Electrical engineering

Bioengineering

CAD

Board design

Tools

CAD software

Job description

Arbor Neuroscience, a nonprofit research organization within the Convergent Research family, is hiring to ensure hardware exists to enable science. The role focuses on mechanical, electrical, and bioengineering across a portable, home-friendly platform, including implants, boards, and benchtop testing, collaborating with an external engineering partner.

You’ll translate scientists' needs into hardware specs, define next-version requirements, and plan in-house vs contracted work.