Algorithm Engineer

🔥 22 minutes ago

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Beacon Biosignals

WebsiteLinkedInAll Job Openings

11 - 50 employees

🧬 Biotechnology

⚕️ Healthcare Insurance

🔬 Science

Biotechnology • Healthcare Insurance • Science

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 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.

🎯 Requirements

• more than 4 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. • experienced 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. • familiar with latest Deep Learning advances (Transformer/ViT, large scale modeling, large model training,...) • follow and adopt best practices in software and ML engineering, including testing, version control, code reviews, documentation, Dockerization, CI/CD, and experiment tracking. • familiar 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.

🏖️ Benefits

• equity • PTO • other benefits