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Salary: USD 150,000 - 170,000 / annual
Beacon Biosignals is transforming precision medicine for the brain through at-home EEG platforms and diagnostics. The company serves life sciences partners in clinical development of therapeutics for neurological, psychiatric, and sleep disorders, while building a comprehensive diagnostics platform combining EEG and cardiopulmonary signals.
You will join Beacon's analytics and machine learning domain, working alongside data scientists, neuroscientists, engineers, and clinicians to scope, build, deploy, and maintain machine and deep learning models that analyze brain and biosignal data for advancing sleep, neurological, and psychiatric therapy development.
Key responsibilities include:
- Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices, including specifications gathering, data curation and labeling, development, failure analysis, production, maintenance, and documentation
- Select and implement the most appropriate method for each problem, knowing when to apply deep learning and when other methods are more effective
- Enhance internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase for reusability
- Spread and improve best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested (unit tests, comprehensive documentation, CI, non-regression testing)
- Present results to key stakeholders and assist them in utilizing algorithms for client engagement
- Support client-facing projects to understand and shape the impact of Beacon algorithms for customers, both for existing deployed algorithms and future development
Beacon emphasizes cultural and scientific impact driven by those who lead by example, seeking contributors who demonstrate innate curiosity, bias toward simplicity, composability, self-service mindset, and deep empathy toward colleagues, stakeholders, users, and patients. The role is 100% remote from anywhere in the U.S., with office hubs in Boston, New York City, and Paris.
REQUIREMENTS:
- More than 4 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with proven track record of bringing algorithms into production
- Experience with digital signal processing (DSP) and statistics; understanding of when to use the right tool for the job (which may not be machine learning or deep learning)
- Proficiency in PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying models
- Familiarity with latest deep learning advances (Transformer/ViT, large scale modeling, large model training)
- Adoption of best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking
- Familiarity with biosignals, medical imaging data, or large time-series datasets, or enthusiasm about learning in the domain
- Ability to thrive in a team environment with strong collaboration, open communication, and continuous feedback
- Ability to distill, discuss, and present complex technical topics appropriately for different audiences, both internally and externally
- Excitement about participating in the entire algorithm development lifecycle spanning scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and client engagement
