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Salary: USD 170,000 - 190,000 / annual
Beacon Biosignals is transforming precision medicine for the brain through at-home EEG and biosignal platforms for clinical development and diagnostics. The company combines EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders.
As a Senior Algorithm Engineer, you will lead the entire biosignal-based algorithm development lifecycle for medical devices. This includes specifications and requirements gathering, data curation and labeling, development, failure analysis, production deployment, maintenance, and documentation. You'll work alongside data scientists, neuroscientists, engineers, and clinicians to scope, build, deploy, and maintain machine and deep learning models that analyze brain and biosignal data.
Key responsibilities include selecting and implementing appropriate methods for each problem, knowing when to apply deep learning versus other techniques. You'll enhance internal ML/DL tools to boost team efficiency, introduce new model architectures, and refine the codebase for reusability. You'll spread best practices to ensure implementations are user-friendly, well-documented, and thoroughly tested with unit tests, CI/CD, and non-regression testing. You'll present results to stakeholders, assist with client engagement, and support client-facing projects to understand algorithm impact.
You bring 5+ years of industry experience in machine learning and deep learning, particularly in health sciences or regulated fields, with a proven track record of production deployments. You have expertise in digital signal processing and statistics, proficiency with PyTorch or other deep learning frameworks, and familiarity with latest advances like Transformers and large-scale modeling. You're experienced with biosignals, medical imaging, or large time-series datasets. You follow best practices in software and ML engineering including testing, version control, code reviews, documentation, Dockerization, and CI/CD. You thrive in collaborative team environments and can distill complex technical topics for diverse audiences.
