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Senior Algorithm Engineer
Beacon Biosignals. 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 .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in machine learning and deep learning for medical devices, with a strong focus on algorithm development, production deployment, and client collaboration. Proficient in implementing best practices in software and ML engineering, including testing, documentation, and CI/CD processes.
Highest-signal resume keywords
Machine LearningDeep LearningDigital Signal ProcessingPyTorchAlgorithm Development Lifecycle
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningDigital Signal ProcessingStatisticsAlgorithm ImplementationModel TrainingData CurationQuality DocumentationTesting Best PracticesVersion Control
Soft Skills
Presentation SkillsClient EngagementCollaboration
Tools & Technologies
PyTorchDockerCI/CDExperiment Tracking
Industry Keywords
Health SciencesBiosignalsMedical ImagingRegulated FieldsTime-Series Datasets
Tech Stack
Tools & technologiesPyTorch
About the role
Key responsibilities & impact- 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 best practices for user-friendly, well-documented, thoroughly tested algorithm implementations, including unit tests, comprehensive documentation, CI, and non-regression testing
- Present results to key stakeholders and assist with algorithm use for client engagement
- Support client-facing projects and shape the impact of Beacon algorithms for customers across deployed and future algorithms
Requirements
What you’ll need- 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 (preferred) or other deep learning frameworks
- Proficiency with current deep learning advances, including Transformer/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 more in the domain
- Ability to distill, discuss, and present complex technical topics appropriately for internal and external audiences
- Excitement to participate in the entire algorithm development lifecycle, including scoping, data wrangling, experimentation, formal validation, quality/regulatory documentation, production deployment, and client collaboration
Benefits
Comp & perks- Equity
- PTO
- First-class remote work experience
- In-person office hubs in Boston, New York City and Paris