Algorithm Engineer VitalConnect is a leader in wearable biosensor technology for wireless patient monitoring in both hospital and remote patient populations. VitalConnect leverages extensive expertise in biomedical engineering, data analytics, chip design, and mobile and cloud software to create technology that supports decision-making paradigms that achieve better health and economic outcomes. VitalConnect’s products are designed for use in a broad range of inpatient and outpatient settings, such as hospital monitoring, post-discharge care, cardiac monitoring and pharmaceutical solutions. The R&D team at VitalConnect is looking for an experienced Algorithm Engineer to help us expand our product features and functionalities that will have a big impact on patient lives and well-being. As an Algorithm Engineer, you will work closely with the members of the cross-functional R&D team to lead and support the development of advanced signal processing and machine learning algorithms deployed in our products that will be crucial to our mission and the success of the company. We are seeking someone with a passion for research and development of advanced algorithms in physiological data analysis and to be a part of a growing team that shapes the future of healthcare. If you feel this is you, we'd love to hear from you.
How you'll contribute:
Developing, analyzing, implementing, and optimizing novel biomedical signal processing and machine learning algorithms from sensor data
Work cross-functionally to define sensor and algorithm specifications, design and development goals, and performance targets
Collaborate with sensor, firmware, mechanical, and software engineers to rapidly develop system concepts to prototype
Conduct exploratory data analysis and visualization
Help design both small and large-scale studies to collect data for algorithm development and demonstrate feasibility of our technologies
Clinically validate algorithms meet intended use and performance requirements using disciplined scientific and statistical methods
Support software and firmware engineers in cloud and embedded implementation of algorithms
Contribute to corporate patent portfolio and technical publications.
Who You Are
4+ years of industry or academic experience in applying advanced signal processing and machine learning algorithms to solving data science problems in real world environment
Demonstrated application of signal processing theory and techniques with experience in signal acquisition, processing and feature extraction in noisy data
Strong hands-on expertise with a variety of machine learning techniques (supervised/unsupervised, clustering, decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning techniques
Very strong programming and analysis capability in Matlab and Python (numpy, scipy, pandas, and scikit-learn)
Good understanding of statistical techniques and concepts
Experience designing studies to test scientific hypotheses with appropriate statistical power.
Experience working with physiological signals and knowledge of the underlying human physiology is desired
Master’s degree with 3+ years of experience or PhD in Computer Science, Electrical Engineering, Biomedical Engineering and related fields with emphasis on signal processing or equivalent with relevant industry experience in medical, physiological, and/or fitness applications
How To Stand Out From The Crowd
Published work in top tier journals and conferences.
Experience in the development, implementation, integration, and testing (pre-clinical or clinical) of physiological-based, end-to-end algorithms in embedded or cloud environments.
Experience with pulse oximetry, non-invasive blood pressure, electrocardiogram, arrhythmia analysis and/or related fields is an advantage