Algorithm Engineer

VitalConnect is seeking an experienced Algorithm Engineer to expand their product features and functionalities, significantly impacting patient lives and overall well-being. The role involves collaborating with a cross-functional R&D team to develop advanced machine learning and deep learning algorithms crucial for the company's mission in healthcare.

Responsibilities:

• Develop, analyze, implement, and optimize novel biomedical machine learning and deep learning algorithms using sensor data
• Own the end-to-end algorithm development lifecycle, encompassing data curation, model development, validation, deployment, and post-market monitoring
• Work cross-functionally to define sensor and algorithm specifications, design and development goals, and key performance targets
• Collaborate with sensor, firmware, mechanical, and software engineers to rapidly translate system concepts into functional prototypes
• Conduct advanced exploratory data analysis and data visualization
• Assist in designing small- and large-scale clinical studies to collect robust data for algorithm training and to demonstrate the feasibility of our technologies
• Clinically validate that algorithms meet intended use and performance requirements using disciplined scientific and statistical methodologies
• Support software and firmware engineering teams in the cloud and embedded implementation of algorithms
• Contribute to the corporate patent portfolio and author technical publications

Requirements:

• Ph.D. in Computer Science, Electrical Engineering, Biomedical Engineering, or a related field with a strong emphasis on deep learning; OR an equivalent combination of education and relevant industry experience in medical, physiological, and/or fitness applications
• 4+ years of combined industry or academic experience applying advanced deep learning and machine learning algorithms to solve complex data science problems in real-world environments
• Strong hands-on expertise with a wide variety of deep learning and machine learning architectures, including a deep understanding of their real-world advantages, limitations, and tuning techniques
• Demonstrated application of signal processing theory, with practical experience in signal acquisition, processing, and feature extraction from noisy data
• Solid grasp of advanced statistical techniques and concepts
• Proven experience designing studies to test scientific hypotheses with appropriate statistical power
• Ability to leverage and operationalize AI-assisted workflows (e.g., code generation, automated analysis, testing) to accelerate development cycles and improve overall system quality and reliability
• Experience with cloud platforms (e.g., AWS) and modern production deployment workflows
• Strong understanding of software engineering best practices, testing frameworks, and reproducibility requirements, particularly within regulated medical systems
• Familiarity working with physiological signals and a working knowledge of underlying human physiology is highly desired