About this role
Professionals who possess a deep empathy toward patients and users, a bias toward simplicity, and innate curiosity will thrive in this environment. Beacon Biosignals operates an at-home EEG platform for clinical development and precision diagnostics focused on neurological, psychiatric, and sleep disorders. The analytics and machine learning team collaborates with neuroscientists, data scientists, engineers, and clinicians to build and maintain models that analyze brain and biosignal data.
As an Algorithm Engineer, you will own the full lifecycle of biosignal-based medical device algorithms, from initial data curation and requirements gathering to production maintenance and documentation. You will determine when to apply deep learning versus simpler methods while refining internal tools to enable rapid experimentation. The position exists to advance therapy development and deliver reimbursable assessments for central nervous system disorders while supporting client-facing projects.
What you will do
- Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices, covering specifications, data curation, labeling, development, and production maintenance.
- Select and implement the most effective method for each problem, choosing between deep learning and alternative techniques depending on the scenario.
- Enhance internal machine learning and deep learning tools to improve team efficiency, introduce new architectures, and refine the codebase for reusability.
- Promote software best practices by ensuring implementations include thorough unit testing, continuous integration, non-regression testing, and clear documentation.
- Present analytical results to key stakeholders and assist them in utilizing algorithms for client engagement.
- Support client-facing initiatives to understand the practical impact of deployed and developing algorithms.
What you need
- Bring more than four years of industry experience in machine learning and deep learning within health sciences or other regulated fields.
- Demonstrate a proven track record of successfully bringing algorithms into production environments.
- Apply background knowledge in digital signal processing and statistics to select appropriate tooling.
- Show proficiency in PyTorch or other deep learning frameworks for model training, development, and deployment.
- Maintain familiarity with recent deep learning advances such as Transformers, ViTs, and large-scale model training.
- Follow software and machine learning engineering best practices including version control, containerization, experiment tracking, and code reviews.
- Possess familiarity or strong enthusiasm for working with biosignals, medical imaging, or large time-series datasets.
Benefits
- Equity
- PTO
Skills and tech stack
Questions candidates ask
What is the remote work policy for this position?
The role is 100 percent remote from anywhere in the U.S. Asynchronous work practices ensure a first-class remote experience, alongside physical office hubs available in Boston, New York City, and Paris.
What is the compensation package offered?
The U.S.-based salary range is $150,000 to $170,000, determined by market data and adjusted based on experience, skills, and location. Base salary is complemented by equity, PTO, and other benefits.
What kind of data and tech stack will I be working with?
You will work with brain and biosignal data, medical imaging data, or large time-series datasets. The team utilizes PyTorch for deep learning alongside modern architectures like Transformers and ViTs.
Who will I be working with on a regular basis?
You will work alongside fellow data scientists, neuroscientists, engineers, and clinicians within the analytics and machine learning domain. You will also present results to key stakeholders and support client-facing projects.
The application is on the official Beacon Biosignals careers page.
Apply on company site