Senior Algorithm Engineer
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Job Description
Senior Algorithm Engineer developing biosignal machine-learning models for Beacon Biosignals’ precision brain medicine platforms. Leading algorithms from data curation through validation, production deployment, and client use.
Responsibilities:
- 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 appropriate methods for each problem, including determining when deep learning or other methods are most effective.
- Enhance internal deep learning and machine learning tools to improve team efficiency, introduce model architectures and algorithmic techniques, and refine code for reusability and rapid experimentation.
- Improve engineering best practices to ensure algorithm implementations are user-friendly, documented, and tested, including unit tests, CI, and non-regression testing.
- Present results to key stakeholders and assist with algorithm use for client engagement.
- Support client-facing projects and help shape the impact of Beacon algorithms for customers and future algorithm development.
Requirements:
- More than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or other regulated fields.
- Proven track record of bringing algorithms into production.
- Experience with digital signal processing (DSP) and statistics.
- Proficiency with PyTorch or other deep learning frameworks for training, developing, and deploying deep learning models.
- Proficiency with current deep learning advances, including Transformers, ViT, large-scale modeling, and large-model training.
- 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 enthusiasm for learning the domain.
- Ability to collaborate in a team environment with open communication and continuous feedback.
- Ability to explain and present complex technical topics appropriately to internal and external audiences.
- Willingness to participate in the full algorithm development lifecycle, including scoping, data wrangling, experimentation, formal validation, quality/regulatory documentation, production deployment, and client collaboration.
Benefits:
- Equity
- Paid time off (PTO)
- First-class remote work experience
- Remote work based anywhere in the U.S.
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