Salary :
The Opportunity
We are looking for a hands-on Test Engineer to help build, validate, and improve the laboratory systems, instrumentation, and test workflows that support our breakthrough neurotechnology platform.
In this role, you will work at the intersection of hardware, software, data acquisition, and experimental science. You will develop and execute test plans, build automated and semi-automated test tools, validate hardware/software behavior, troubleshoot system issues, and help ensure that experimental platforms are reliable, repeatable, and ready to support fast-moving R&D.
You will partner closely with hardware, software, research, data science, and product teams to turn early prototypes into robust, usable test systems. This includes testing instrument control software, validating data acquisition pipelines, supporting hardware/software integration, documenting system performance, and improving confidence in experimental results through structured testing and validation.
Key Responsibilities
- Design and build Python-based software to control, coordinate, monitor, and visualize signals from sophisticated laboratory hardware.
- Design and build desktop user interfaces and internal tools to this end
- Develop software abstraction layers over vendor SDKs, PyVISA/SCPI, serial, USB/Ethernet, DAQ systems, analog/digital I/O, and equipment-specific APIs.
- Implement experiment orchestration software that coordinates multiple instruments, manages timing, handles triggers, and supports synchronized data acquisition.
- Test and validate software used to control, coordinate, monitor, and visualize signals from sophisticated laboratory hardware.
- Work with hardware engineers to define and document hardware/software interface specifications
- Build reliable data acquisition and logging pipelines for raw signals, instrument state, metadata, calibration information, and experimental outputs in collaboration with data scientists/engineers.
- Manage software environments, drivers, dependencies, and deployment across laboratory computers and hardware-connected systems.
- Write tests, simulations, and validation tools to improve reliability, maintainability, and confidence in hardware/software behavior.
- Troubleshoot issues spanning device communication, hardware integration, data acquisition, user interfaces, and experiment workflows.
- Partner with hardware, research, data science, and product teams to turn early prototypes into robust, usable laboratory systems.
- Help establish engineering patterns, documentation practices, and code quality standards as the team grows.
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