Senior Algorithm Engineer

Role overview

Senior Algorithm Engineer working with cross-functional teams (data scientists, neuroscientists, engineers, clinicians) to develop and maintain machine learning and deep learning models for brain/biosignal analysis. You’ll cover the full algorithm lifecycle, from requirements to production and documentation, including client-facing work.

Responsibilities

• Lead and participate in the biosignal-based algorithm development lifecycle for medical devices:
  • Specifications/requirements gathering
  • Data curation and labeling
  • Algorithm development and experimentation
  • Failure analysis
  • Production deployment and maintenance
  • Documentation (including quality/regulatory materials)
• Select and implement the right method per problem, using deep learning when appropriate and classical/statistical methods when better.
• Enhance internal ML/DL tooling to improve team efficiency:
  • Introduce new model architectures and algorithmic techniques
  • Refine the codebase for reusability to enable rapid experimentation

Requirements

• 5+ years of industry experience in machine learning/deep learning, preferably in health sciences or other regulated fields.
• Strong proficiency with PyTorch (or other deep learning frameworks) for training, developing, and deploying models.
• Demonstrated expertise with modern deep learning methods (e.g., Transformers/ViT, large-scale modeling/training).
• Experience with digital signal processing (DSP) and statistics; ability to choose non-ML approaches when they fit.
• Collaboration-focused mindset and strong communication skills for both internal and external stakeholders.
• Experience spanning scoping, data wrangling, experimentation, validation, production deployment, and client collaboration.
• Software/ML engineering best practices:
  • Testing, version control, code reviews, documentation
  • Dockerization, CI/CD, experiment tracking

Nice-to-haves

• Experience with biosignals, medical imaging, or large time-series datasets (or strong motivation to learn the domain).