Senior Algorithm Engineer

Role overview Develop and maintain algorithms that analyze EEG and other physiological signals for research and diagnostic applications related to sleep and neurological or psychiatric conditions. You will work across the full algorithm lifecycle, from defining requirements and preparing data through experimentation, validation, deployment, and ongoing support, in collaboration with data scientists, engineers, neuroscientists, and clinicians.

Responsibilities - Lead or contribute to algorithm projects from requirements gathering and data curation through development, failure analysis, production, maintenance, and documentation. - Choose suitable statistical, signal-processing, machine-learning, or deep-learning approaches for each problem. - Improve internal ML tools, explore architectures and techniques, and make code more reusable to support efficient experimentation. - Establish reliable engineering practices, including tests, documentation, continuous integration, and regression checks. - Present findings to stakeholders and help client-facing teams understand how algorithms can be applied. - Support deployed algorithms and help shape future development based on project and customer needs.

Requirements - More than five years of industry experience in machine learning and deep learning, ideally in health sciences or another regulated area, with algorithms brought into production. - Experience with digital signal processing and statistics, and sound judgment about when simpler methods are more appropriate than ML. - Proficiency with PyTorch or a comparable deep-learning framework for training and deploying models. - Familiarity with modern deep-learning methods, such as transformers or vision transformers, and large-scale model training. - Strong software and ML engineering practices, including version control, code review, testing, documentation, containers, CI/CD, and experiment tracking. - Ability to collaborate and explain technical results clearly to internal and external audiences.

Nice to have - Experience with biosignals, medical imaging, or large time-series datasets; willingness to learn the domain is also noted. - Experience with formal validation and quality or regulatory documentation.

Benefits and work setup - Fully remote within the United States, with office hubs available in Boston, New York City, and Paris. - Source lists a base salary range of $170,000–$220,000, plus equity, paid time off, and other benefits.