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Beacon BiosignalsBeacon BiosignalsBoston, MA

Senior Algorithm Engineer

Lead the full lifecycle of biosignal-based ML and deep learning algorithm development for medical devices at an EEG platform company. Requires 5+ years of ML/DL experience in regulated fields, DSP/statistics proficiency, PyTorch expertise, and strong software engineering practices.

170k – 190k/yr
Remote5+ YOEML Engineering

About the role

What success looks like

  • Participate in and lead the entire biosignal-based algorithm development lifecycle for medical devices including specifications and requirements gathering, data curation and labeling, development, failure-analysis, production, maintenance, and documentation.
  • Select, implement, and develop the most appropriate method for each problem, knowing when to apply deep learning techniques and when other methods are more effective.
  • Enhance our internal deep learning and machine learning tools to boost team efficiency, introduce new model architectures and algorithmic techniques, and refine the codebase to encourage reusability where needed to enable rapid experimentation.
  • Spread and 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.
  • Present results to key stakeholders and assist them in utilizing algorithms for client engagement.
  • 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

  • More than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields, with a proven track record of bringing algorithms into production.
  • Experience with digital signal processing (DSP) and statistics and care about using the right tool for the job, which in many cases might not be machine learning or deep learning.
  • Proficient in using PyTorch (preferred) or other deep learning frameworks for training, developing, and deploying deep learning models.
  • Proficient with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training, ...)
  • Follow and spread best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking.
  • Experience with biosignals, medical imaging data, or large time-series datasets, or are enthusiastic about learning more in the domain.
  • Thrive in a team environment, recognizing that collaboration, open communication, and continuous feedback are essential for collective success.
  • Able to distill, discuss, and present complex technical topics in a way that is appropriate for the audience at hand, both internally and externally.
  • 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.

Compensation

The US-based salary range for this role is $170,000 – $190,000. 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.

Skills

PyTorchDeep LearningMachine Learningdigital signal processingTransformersvitDockerCI/CDbiosignalstime-series dataStatistics

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