Real-Time Neural Signal Processing & ONNX Runtime Engineer

Job Title: Real-Time Neural Signal Processing & ONNX Runtime Engineer
Workplace Type: Remote
Employment Type: Full-time / Contractor
About the Role:
The James Bridge is an open-source brain-computer interface (BCI) framework focused on high-throughput EEG signal acquisition, distributed data streaming, and ultra-low-latency neural decoding. We are looking for an engineer to optimize our telemetry pipelines, manage stateful ONNX model inference at the edge, and refine multi-channel neural stream synchronization.
Key Responsibilities:

• Architect and profile low-latency EEG streaming pipelines using the Lab Streaming Layer (LSL) protocol.


• Implement, quantize, and benchmark stateful ONNX step-inference models for real-time motor imagery classification and artifact removal.


• Maintain sub-15ms pipeline latency across variable-rate bio-signal ingest buffers.


• Collaborate on core open-source repository architecture, documentation, and continuous integration testing across Linux and POSIX-compliant environments.


• Develop mock data harnesses and unit tests simulating multi-channel dry/wet electrode setups.
  Requirements & Qualifications:


• BS or MS in Computer Science, Biomedical Engineering, Neuroscience, or equivalent practical experience.


• Solid programming experience in Python, C++, or Rust with a focus on systems performance and memory safety.


• Practical understanding of digital signal processing (bandpass filtering, notch filters, wavelet decomposition, ICA).


• Direct experience deploying models with ONNX Runtime, PyTorch, or TensorRT.


• Familiarity with hardware abstraction layers and streaming telemetry protocols (LSL, MQTT, or ZeroMQ).
  Compensation & Perks:


• Competitive hourly contractor rate ($65–$95/hr, based on experience).


• Fully remote, asynchronous workflow.


• Flexible hours and hardware testing stipend.