R&D Algorithm Engineer – Health Technologies

About Us

Vena Vitals is on a mission to transform patient care through better cardiovascular monitoring. We make a small wearable device that monitors blood pressure continuously. Unlike other BP monitors that only take a snapshot in time we record the entire dynamic movie to track changes that can be life-saving. We have strong early clinical results and we’re now expanding our clinical studies across multiple sites around the country. From the operating room to the home we plan to become the most accurate and actionable cardiovascular monitoring and management system to help improve the lives of over a billion patients across the world each year.

Job Description

You will develop algorithms that incorporate multiple continuous biomedical signals into relevant insights. You will develop tools to enhance signal and subtract out common noise artifacts as well as extract insights from continuous biomedical signals (features events and trends) both off-line and in real time.

You will be engaged in solving problems that currently do not have well defined solutions and you’ll take the reins to own and steer your deliveries while also supporting others in a fast-paced encouraging and dynamic environment.

Key Qualifications

• 4+ years of experience working with physiological signals (extracting cleaning and analysis of datasets). Domain knowledge of cardiovascular system and hemodynamics is a plus.
• Experience working with complex data sets that have limited sample sizes.
• Strong background in exploratory and statistical data analysis. Knowledge of design of experiments is a plus.
• Experience in developing algorithms that handle time-series data which can include but not limited to training and evaluating machine/deep learning models (e.g. tree-based models LSTM recurrent neural networks).
• Excellent fluency in a high-level programming language (Python C/C++ and/or Matlab)
• Knowledge of common ML frameworks (scikit-learn pandas and deep learning toolboxes such as TensorFlow PyTorch Caffe etc) is a plus.
• Experience in one or more of the following is a plus: signal processing multimodal sensing sensor fusion time series time-frequency analysis and dynamical systems
• Masters/PhD in Biomedical Engineering Electrical Engineering Computer Science Mathematics Physics or related fields or equivalent work experience.

Additional Qualifications

• Expected to perform well in a fast-paced environment to execute on the tasks assigned to meet the production deadlines and at the same time to explore independently new innovative ideas.
• Ability to communicate highly technical results and methodologies along with working cross-functionally with a wide range of people
• Ability to review literature related to projects and integrate relevant information.
• Knowledge of medical instrumentation is a plus