The Role

Neuralink’s next generation surgical robot will perform brain surgery at scale, installing hundreds of tiny threads into the brain to enable brain computer communication.

You’ll own building out the robot test fleet. Break robots into testable components, build rigs that reproduce operating conditions, perform surgeries on brain proxies, and automate accelerated life testing (ALT). Your fleet gives us the evidence to ship new capabilities regularly and safely. When the robot misbehaves, you’re in the lab figuring it out.

What you’ll do

• Bring up, instrument, and run robots and component test rigs.
• Hunt failures across mechanics, electronics, firmware, and software.
• Automate routine robot V&V, test setup, execution, recovery, and results.
• Design and build fixtures, sensing, and logging, with safe operating procedures and fast turnaround.
• Work with Sim and HIL engineers to make the models and tests match reality.
• Turn real failures into repeatable regression tests so we stop burning hardware time on known bugs.

One day you’ll be chasing a failure that happened once, the next you’ll be building systems that run the same way every time. We need someone who can do both and knows which one the day calls for.

Note: The team is hiring engineers at all levels, both junior and senior. What matters most is evidence of exceptional abilities and a drive to succeed.

What we’re looking for

• Hands-on robotics experience. You’ve made a robot work, broken it, and made it work again.
• Enough Python to automate tests and analyze results, and a basic understanding of Rust.
• Hands-on experience with motor drives, encoders, sensors, and hardware interfaces such as Ethernet, SPI, I²C, UART, or EtherCAT.
• Comfortable reading schematics, building instrumented fixtures, and using oscilloscopes, logic analyzers, and data acquisition systems to diagnose failures.
• High agency on hardware, comfortable with noise, intermittent faults, and failures that resist reproduction.
• Discipline about repeatability, traceability, and recording what actually happened.
• Judgment to know when a robot is ready, and the diligence to bring the evidence to back it up.
• Effective at using AI agents to build tooling, analyze data and automate failure investigations.