Senior Algorithm Engineer

Role Description

Beacon Biosignals is seeking a Senior Algorithm and Machine Learning engineer! As part of Beacon's analytics and machine learning domain, you'll work alongside fellow 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.
• Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and 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 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 of Beacon algorithms for customers, both for existing deployed algorithms and future algorithm development.

Qualifications

• More than 5 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, with a focus on using the right tool for the job.
• Proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
• Proficient with the latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...).
• Familiar with best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
• Experience with biosignals, medical imaging data, or large time-series datasets, or enthusiasm for learning more in the domain.
• Ability to distill, discuss, and present complex technical topics appropriately for the audience.
• Excitement to participate in the entire algorithm development lifecycle, including scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, and production deployment.

Requirements

• Thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.

Benefits

• US-based salary range for this role is $170,000 – $190,000.
• Salary ranges are determined using current market compensation data for this role and adjusted based on experience, skills, and location.
• The base salary is one component of the total compensation package, which includes equity, PTO, and other benefits.