Senior Algorithm Engineer
The Senior Algorithm Engineer leads development and production deployment of machine and deep learning algorithms for biosignal and medical-device applications. The role requires 5+ years of industry experience, DSP and statistics expertise, PyTorch proficiency, and familiarity with regulated health or similar domains.
About the job
Responsibilities
- Lead the full biosignal-based algorithm development lifecycle for medical devices, including requirements gathering, data curation and labeling, development, failure analysis, production, maintenance, and documentation.
- Select, implement, and develop appropriate algorithmic methods, including deep learning and traditional approaches.
- Enhance internal machine learning and deep learning tools, introduce model architectures and algorithmic techniques, and improve code reusability.
- Establish best practices for user-friendly, documented, tested algorithm implementations, including unit testing, continuous integration, and non-regression testing.
- Present results to stakeholders and support client engagement.
- Support client-facing projects and help shape the impact of deployed and future algorithms.
Requirements
- More than 5 years of industry experience in machine learning and deep learning, particularly in health sciences or regulated fields.
- Proven experience bringing algorithms into production.
- Experience with digital signal processing and statistics.
- Proficiency with PyTorch or other deep learning frameworks.
- Knowledge of modern deep learning advances, including Transformers, Vision Transformers, large-scale modeling, and large-model training.
- Experience with software and machine learning engineering best practices, 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.
- Strong collaboration, communication, and technical presentation skills.
- Ability to contribute across scoping, data wrangling, experimentation, formal validation, quality and regulatory documentation, production deployment, and client collaboration.
Compensation and Benefits
- US-based salary range: $170,000–$190,000 USD.
- Compensation includes base salary, equity, paid time off, and other benefits.
Skills
Machine Learning, Deep Learning, Digital Signal Processing, Statistics, PyTorch, Transformers, Vision Transformers, Large-Scale Modeling, Docker, Continuous Integration, Continuous Deployment, Experiment Tracking, Biosignals, Medical Imaging, Time-Series Data
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