Precision Neuroscience is building a next-generation brain-computer interface for people living with neurological conditions. Its first product, Layer 7, is designed to help people with severe paralysis operate digital devices using only their thoughts. Founded in 2021, the company has raised more than $180 million and has initiated human trials with hospitals across the country.

About the role

This role analyzes and improves Precision's end-to-end signal processing chain, working closely with EE design engineers alongside firmware, ML and software engineers on BCI signal acquisition systems.

What you will do

• Analyze the end-to-end sensor signal chain, from sensor elements through to ML feature extraction.
• Analyze and design advanced signal processing methods for acquisition improvements, such as adaptive filters for interference rejection.
• Correlate and model practical device performance against bench device performance.

What they are looking for

• Strong understanding of analog and digital signal processing including filters, sampling and analog to digital conversion, plus statistical signal processing.
• Solid knowledge of analog signal processing imperfections such as noise, interference and component variations.
• Knowledge of control systems and feedback fundamentals.
• Experience with system modeling and simulation frameworks such as Python, MATLAB, Simulink, SystemC or SystemVerilog.
• Embedded signal processing experience including fixed-point optimization for FPGA or DSP implementation.
• Working knowledge of PyTorch; digital communication fundamentals, SERDES and on-device ML are a plus.

The role can be based in the Santa Clara, New York, Chicago or Framingham office. Remote workers cannot be considered.