Machine Learning Engineer, Biosignals

Beacon Biosignals is transforming precision medicine for the brain, from clinical development to clinical care. For Life Sciences partners, we offer the leading at-home EEG platform for clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our Diagnostics business is building the most comprehensive at-home platform for precision diagnostics, combining EEG and cardiopulmonary signals to deliver reimbursable assessments for sleep and central nervous system disorders. Together, we're changing the way patients are diagnosed and treated for any disorder that affects brain physiology.

Beacon Biosignals is seeking a Machine Learning engineer!

As part of Beacon's analytics and machine learning team, you'll work with data scientists, neuroscientists, engineers, and clinicians to build, deploy, and maintain deep learning models that analyze brain and biosignal data for advancing sleep, neurological, and psychiatric therapy development.

At Beacon, we've found that cultural and scientific impact is driven most by those who lead by example. As such, we're always seeking out new contributors whose work demonstrates innate curiosity, a bias toward simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy toward colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.

This role is 100% remote from anywhere in the U.S. Beacon's robust asynchronous work practices ensure a first-class remote work experience, but we also have in-person office hubs in Boston and New York City.

What success looks like

• Participate in and lead the machine learning algorithm development lifecycle for medical devices, including requirements definition, data curation, model development, production deployment, maintenance, and documentation.
• Select, develop, and implement the most appropriate numerical method for each problem. Have a good judgement in when to apply rule-based algorithms, traditional machine learning, and deep learning techniques.
• Present results clearly to key stakeholders and assist them in utilizing algorithms for client engagement.
• Enhance internal machine learning tools to boost efficiency. Introduce new model architectures and algorithmic techniques,. Refine the codebase to improve reusability for rapid experimentation.
• Improve our best practices to ensure algorithm implementations are user-friendly, well-documented, and thoroughly tested, including unit tests, comprehensive documentation, CI, and non-regression testing.
• Support the client-facing projects to understand and shape the impact Beacon algorithms have for our customers, both for existing deployed algorithms, and future algorithm development.

What you will bring

• You have an M.S. or Ph.D. (preferred) in neuroscience, biological physics, or a related quantitative field.
• You have at least 4 years of industry experience in developing and deploying machine learning and deep learning models, particularly in biotech, health sciences or other regulated fields.
• You enjoy tackling both scientific and engineering problems with large-scale data. You enjoy the full cycle of ML/AI development from research to production deployment.
• You are an expert in machine learning methodologies, such as supervised learning, event detection, training, evaluation, leakage prevention, and hyperparameter tuning.
• You are proficient in digital signal processing (DSP) and statistical analysis.
• You are proficient in using deep learning frameworks, such as PyTorch (preferred) and TensorFlow.
• You are proficient in Python and Julia (nice to have).
• You have working experience with large-scale biological data such as EEG, biosignals from wearables, genomic data (NGS/proteomics), or medical imaging data.
• You are an expert in one or more machine learning methods. You are broadly familiar with the latest Deep Learning approaches, such as transformers architectures, foundation models, generative models.
• You follow best practices in ML software engineering, including version control, code reviews, testing, documentation, CI/CD, containerization, and experiment tracking.
• You care about using the right tool for the job, which in many cases might not be machine learning or deep learning.
• You are a team player. You recognize that collaboration, open communication, and continuous feedback are essential for collective success.
• You are a good communicator. You can distill, discuss, and present complex technical topics in a way that is appropriate for the internal or external audience.
• You are excited to participate in the entire algorithm development lifecycle, which spans scoping, data wrangling, algorithm development/experimentation, formal validation, quality/regulatory documentation, production deployment, and working with clients who might benefit from these algorithms.

The US-based salary range for this role is $150,000 – $170,000. 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.

At Beacon, we've found that cultural and scientific impact is driven most by those that lead by example. As such, we're always seeking new contributors whose work demonstrates an avid curiosity, a bias towards simplicity, an eye for composability, a self-service mindset, and - most of all - a deep empathy towards colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact.