Mechatronics & Robotics Engineer — Associate

Stanford Reglab; United States; On-site; USD 133,000 - 158,000; Full time

Job summary

Stanford University is seeking an Engineer Associate to develop advanced robotic hardware and intracortical brain‑ interfacing technology. You will prototype mechatronic systems, contribute to neural recording modules, and support scalable assembly processes for lightweight, precisely controlled interfaces.

The role sits at the intersection of neuroscience, engineering, software, and AI, collaborating with neuroscientists and engineers under the Tolias lab.

Qualifications

• Bachelor’s degree in engineering or related field with six years of relevant experience or equivalent.
• Experience designing and implementing robotic systems, especially haptic interfaces or surgical robotics.
• Experience with microassembly systems and high‑precision robot arms.
• Proficient CAD skills in modern tools and rapid prototyping knowledge.

Responsibilities

• Develop backdrivable robotic manipulanda for physical interactions within software‑defined virtual environments.
• Create modular neural recording and behavior systems with scalable assembly approaches.
• Advance miniaturized actuation and control, including piezoelectric motors and real‑time vision monitoring.
• Maintain design libraries and documentation for versioning and collaboration.
• Collaborate with systems engineers and researchers to meet evolving experimental needs.

Skills

Robotic systems design

Mechatronics

CAD tools

Electronics & circuitry

Software development

Rapid prototyping

Machine shop experience

Fabrication tolerances

Interdisciplinary collaboration

Neuro‑AI interest

Education

Bachelor's degree in engineering

Tools

OnShape

SolidWorks

Fusion 360

PCB Design

Embedded cameras

Job description

Stanford University is seeking an Engineer Associate to develop advanced robotic hardware and intracortical brain‑ interfacing technology. You will prototype mechatronic systems, contribute to neural recording modules, and support scalable assembly processes for lightweight, precisely controlled interfaces.

The role sits at the intersection of neuroscience, engineering, software, and AI, collaborating with neuroscientists and engineers under the Tolias lab.