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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 Machine Learning Engineer, you will be a core member of Beacon's analytics and machine learning domain, working alongside data scientists, neuroscientists, engineers, and clinicians. You'll own the full lifecycle of biosignal-based algorithm development for medical devices, from specifications and requirements gathering through data curation, model development, failure analysis, production deployment, maintenance, and documentation.
Key responsibilities include:
- Lead algorithm development across the entire lifecycle, selecting and implementing appropriate methods (deep learning, classical ML, or signal processing) for each problem
- Enhance internal ML/DL tools and infrastructure, introduce new model architectures, and refine codebases for reusability and rapid experimentation
- Establish and spread best practices ensuring algorithms are user-friendly, well-documented, thoroughly tested (unit tests, CI/CD, non-regression testing), and production-ready
- Present technical results to stakeholders and support client-facing projects to understand algorithm impact
- Collaborate with cross-functional teams to shape the impact of algorithms for customers, both for deployed systems and future development
You bring 4+ 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 strong expertise in digital signal processing and statistics, proficiency with PyTorch or similar frameworks, and familiarity with modern deep learning advances (Transformers, ViT, large-scale modeling). You follow software and ML engineering best practices including testing, version control, CI/CD, and experiment tracking. Experience with biosignals, medical imaging, or large time-series datasets is valued. You thrive in collaborative environments, communicate complex technical topics clearly to diverse audiences, and are excited about the full algorithm development lifecycle in a regulated medical device context.
