Senior Algorithm Engineer

Role overview A senior individual contributor role focused on building and shipping machine learning and deep learning models that analyze brain and biosignal data for clinical development and diagnostic applications in sleep, neurological, and psychiatric health. The position spans the full algorithm lifecycle, from scoping and data curation through validation, production deployment, and ongoing client-facing support. It also carries responsibility for mentoring peers, raising engineering quality, and shaping how the broader analytics team collaborates.

Responsibilities - Lead end-to-end algorithm development for biosignal-based medical devices, including requirements gathering, data labeling, model development, failure analysis, validation, deployment, and documentation. - Select and implement the most suitable method for each problem, applying deep learning where it fits and classical approaches such as digital signal processing or statistics where they are more appropriate. - Improve shared deep learning and machine learning infrastructure, introduce new architectures, and refactor codebases to make experimentation faster and more reusable. - Promote strong engineering practices, including testing, code review, documentation, CI pipelines, non-regression testing, Dockerization, version control, and experiment tracking. - Present results to internal stakeholders, support client engagements, and help translate algorithm capabilities into value for partner organizations.

Requirements - More than five years of industry experience in machine learning and deep learning, with a track record of bringing algorithms into production, preferably in health sciences or other regulated domains. - Solid grounding in digital signal processing and statistics, with the discipline to choose the simplest method that solves the problem. - Proficiency with PyTorch or comparable deep learning frameworks for training, developing, and deploying models. - Familiarity with current deep learning advances such as Transformers, vision transformers, and large-scale model training. - Experience working with biosignals, medical imaging data, or other large time-series datasets, or strong enthusiasm to learn the domain quickly. - Comfort owning the complete lifecycle, including data wrangling, experimentation, validation, regulatory documentation, production deployment, and client interaction.

Benefits and work setup - Fully remote position based anywhere in the United States. - US-based salary range of $170,000 to $220,000, with equity, PTO, and other benefits forming part of the total compensation package.