Senior Algorithm Engineer

Role overview A senior engineering position focused on building, validating, and deploying machine learning and deep learning algorithms that analyze physiological biosignal data to support advances in sleep, neurological, and psychiatric care. The role spans the full algorithm lifecycle for regulated medical applications, working in close collaboration with data scientists, neuroscientists, engineers, and clinicians.

Responsibilities - Lead end-to-end algorithm development for medical-grade biosignal products, from requirements gathering and data curation through production deployment, maintenance, and documentation. - Select the most effective method for each problem, applying deep learning where it fits and classical DSP or statistical approaches where they are more appropriate. - Develop and improve internal machine learning tooling, introduce new architectures, and refine shared code to enable rapid, reproducible experimentation. - Establish and spread best practices for testing, documentation, CI/CD, containerization, and non-regression checks so algorithms remain robust and well-supported. - Present findings and analytical results to technical and non-technical stakeholders, and support client-facing work that translates models into real-world impact.

Requirements - More than five years of industry experience in machine learning and deep learning, ideally in health sciences or another regulated environment, with shipped production algorithms. - Strong background in digital signal processing and statistics, with judgment about when machine learning is and is not the right tool. - Proficiency in PyTorch or comparable deep learning frameworks for training, developing, and deploying models. - Familiarity with modern deep learning advances such as transformers, vision transformers, and large-scale or large-model training. - Solid software engineering habits including unit testing, version control, code review, Dockerization, CI/CD, and experiment tracking. - Experience with biosignals, medical imaging, or large time-series datasets, or strong enthusiasm to learn the domain quickly. - Comfort communicating complex technical topics clearly to varied audiences and collaborating in a team-oriented environment.

Nice to have - Enthusiasm for participating across the entire algorithm lifecycle, including formal validation, regulatory-quality documentation, and direct customer interaction.

Benefits and work setup - Fully remote role based anywhere in the United States. - US-based salary range of $170,000 to $190,000, with equity, paid time off, and additional benefits included in the total compensation package. - Compensation adjusted based on experience, skills, and location.