Algorithm Engineer

Beacon Biosignals is on a mission to revolutionize precision medicine for the brain. We are the leading at‑home EEG platform supporting clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker discovery and implementation. Beacon’s Clinico‑EEG database contains EEG data from nearly 100,000 patients, and our cloud‑native analytics platform powers large‑scale RWD/RWE retrospective and predictive studies. Beacon Biosignals is changing the way patients are treated for any disorder that affects brain physiology.

We work asynchronously to create a first‑class remote experience, while also maintaining in‑person office hubs in Boston, New York City, and Paris.

What Success Looks Like

• Participate in and lead the entire biosignal‑based algorithm development lifecycle for medical devices, including specifications, requirements gathering, data curation and labeling, development, failure analysis, production, maintenance, and documentation.
• Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.
• Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability for rapid experimentation.
• Spread and improve best practices to ensure algorithm implementations are user‑friendly, well‑documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and 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 Beacon algorithms have for customers, both for existing deployed algorithms and future development.

What You Will Bring

• More than 4 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production.
• Experience with digital signal processing (DSP) and statistics, and an understanding that the right tool may not always be machine learning or deep learning.
• Proficiency in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying models.
• Familiarity with the latest deep learning advances (Transformers/ViT, large‑scale modeling, large‑model training, etc.).
• Adoption of best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
• Comfort with biosignals, medical imaging data, or large time‑series datasets, or enthusiasm for learning more in the domain.
• Thriving in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.
• Ability to distill, discuss, and present complex technical topics in a way that is appropriate for the audience, both internally and externally.
• Excitement to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients.

The base salary range for this role is determined based on past experience, specific skills, and qualifications. The base salary is one component of the total compensation package, which includes equity, PTO, and other benefits.