Edwards Lifesciences Veterans Jobs

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Edwards Lifesciences Machine Learning Staff Engineer in Irvine, California

The Machine Learning Staff Engineer leverages research, design and development experience in new medical device and product development. We are seeking for an exceptional and self-motivated Machine Learning Engineer to join our growing team in the Applied Machine Learning Group. Responsibilities include applying machine learning, time series models, physiological signal processing, and human physiology to develop algorithms for minimally invasive and noninvasive critical care patient monitoring products. Responsible for performing research and feasibility of new concepts, conducting animal studies and R&D clinical trials, analyzing data, drawing conclusions and preparing final reports and presentations.

Required Qualifications:

  • Master's degree in biomedical engineering or electrical engineering and 5+ years of professional experience with a strong background in mathematics, machine learning, and signal processing is required

  • 4+ years of experience building ML models and putting into production

  • Strong clinical and engineering communication skill set is needed to facilitate working with Edwards teams and executives, physician collaborators and principal investigators

  • Strong theoretical and applied background in Digital Signal Processing (DSP), mathematical modeling and algorithm development for biomedical applications

  • Strong experience in scripting languages, such as MATLAB and Python for prototyping, testing and validation of signal processing algorithms and model development

  • Must be a highly motivated self-starter who is able to achieve results with minimal direction.

  • Requires a high-energy individual who has excellent teamwork, partnering, and negotiation skills

  • Must be proactive and creative in achieving goals

Preferred Qualifications:

  • PhD in biomedical engineering or electrical engineering and 2+ years of professional experience is strongly preferred

  • Experience with deep learning techniques (CNN, LSTM, RNN, etc) is a plus

  • High degree of familiarity with Sklearn, TensorFlow/Keras, Pytorch

  • Understanding of some big data tools and experience with cloud-based providers (AWS, Azure) is a plus

  • Strong theoretical and applied background in human physiology and anatomy is a plus

  • Experience in hemodynamics and cardiovascular biomechanics is a plus

  • Experience working with high resolution time series data (ECG, arterial blood pressure, etc) is a plus

  • Impeccable documentation of work results - experience in writing scientific reports and papers is a plus

  • Advanced problem-solving, organizational, analytical and critical thinking skills

  • Extensive understanding of all fundamental principles of Algorithm development for biomedical application

  • Must be able to work in a team environment, including frequent inter-organizational and outside customer contacts

  • Represents organization in providing solutions to difficult technical issues associated with specific projects

Edwards is an Equal Opportunity/Affirmative Action employer including protected Veterans and individuals with disabilities.

Edwards Lifesciences is the global leader in patient-focused medical innovations for structural heart disease, as well as critical care and surgical monitoring. Driven by a passion to help patients, the company collaborates with the world's leading clinicians and researchers to address unmet healthcare needs, working to improve patient outcomes and enhance lives. Headquartered in Irvine, California, Edwards Lifesciences has extensive operations in North America, Europe, Japan, Latin America and Asia and currently employs over 15,000 individuals worldwide.

For us, helping patients is not a slogan - it's our life's work. From developing devices that replace or repair a diseased heart valve to creating new technologies that monitor vital signs in the critical care setting, we focus on helping patients regain and improve the quality of their life.