Senior Algorithm Engineer

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Beacon Biosignals

WebsiteLinkedInAll Job Openings

11 - 50 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

Beacon Biosignals is a company focused on powering precision medicine for the brain. Their EEG neurobiomarker platform is engineered to accelerate clinical trials and enable new treatments for patients with neurological and psychiatric diseases. The platform captures a rich array of the brain's activity in real time and utilizes machine learning to analyze EEG data for treatment efficacy, dose selection, and population stratification. Beacon Biosignals partners with biopharma companies, academic medical centers, and neurotechnology developers to improve the diagnosis and treatment of neurological and psychiatric diseases.

📋 Description

• 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.