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Precision Neurosciencetoday

EE Systems Engineer

On-site · Chicago, Illinois, United States or Santa Clara, California, United States

Type
Full Time
Level
Mid Level
Education
Not Specified
Company size
Startup

Job Summary

EE Systems Engineer to analyze and improve end-to-end BCI signal acquisition and processing chains. Collaborate with EE, FW, ML, and SW teams to design and implement advanced signal processing methods (e.g., adaptive filters for interference rejection) and model device performance versus bench performance. Role involves end-to-end sensor signal chain analysis from sensors to ML feature extraction, with a focus on analog/digital signal processing, noise and interference characterization, and system-level design. Based in Santa Clara or Chicago offices in the US; no remote work.

Required Qualifications

  • Strong understanding of analog and digital signal processing (filters, sampling, analog to digital conversion)
  • Experience with adaptive filters for interference rejection
  • Knowledge of control systems and feedback fundamentals
  • Experience with system modeling and simulation frameworks (Python / MATLAB / Simulink / SystemC / SystemVerilog)
  • Experience with embedded signal processing, including fixed-point optimization for FPGA or DSP implementation
  • Working knowledge of ML frameworks (PyTorch)
  • Knowledge of digital communication fundamentals and SERDES is a plus
  • Experience with on-device ML is a plus
  • Collaborative experience with EE design, FW, ML, and SW teams

Desired Qualifications

  • Experience with FPGA or DSP implementation
  • On-device ML experience
  • Experience with PyTorch
  • Knowledge of digital communication fundamentals and SERDES
  • Experience with system modeling and simulation frameworks (Python / MATLAB / Simulink / SystemC / SystemVerilog)
  • Diversity and inclusive culture experience is valued
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Precision Neuroscience

EE Systems Engineer

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