Senior Biosignal ML Engineer (Remote)

United States Digital Space LLC

United States

Remote

USD 140,000 - 190,000

Full time

14 days+
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Job summary

Beacon Biosignals is building an at-home EEG platform for brain-related therapeutic development, offering remote work with in-person hubs in Boston, NYC, and Paris. The ML Engineer will scope, build, deploy, and maintain models analyzing brain and biosignal data for sleep and neurological therapies.

The role requires 4+ years in ML/DL in regulated settings, proficiency in PyTorch, and strong collaboration across cross-disciplinary teams.

Qualifications

  • 4+ years of ML/DL experience in health sciences or regulated fields.
  • Experience with DSP and statistics; knowing when not to use ML.
  • Proficient in PyTorch or other DL frameworks.
  • Familiar with Transformer/ViT and large-scale modeling.
  • Familiar with biosignals or large time-series datasets.
  • Strong software engineering practices: testing, version control, docs, Dockerization, CI/CD, experiment tracking.

Responsibilities

  • Lead the biosignal-based algorithm development lifecycle from data curation to deployment.
  • Select and develop methods, balancing ML with DSP/statistics.
  • Improve internal ML tools, architectures, and reusable code.
  • Document, test, and validate algorithms with CI/non-regression tests.
  • Present results to stakeholders and support client engagements.
  • Collaborate with data scientists, neuroscientists, engineers, and clinicians.

Skills

Team collaboration
Communication
Problem solving

Tools

PyTorch
Docker
CI/CD
Experiment tracking

Job description

Beacon Biosignals is building an at-home EEG platform for brain-related therapeutic development, offering remote work with in-person hubs in Boston, NYC, and Paris. The ML Engineer will scope, build, deploy, and maintain models analyzing brain and biosignal data for sleep and neurological therapies.

The role requires 4+ years in ML/DL in regulated settings, proficiency in PyTorch, and strong collaboration across cross-disciplinary teams.

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