About This Role:iRhythm is seeking a Machine Learning Scientist to help advance the intelligence behind our diagnostic and biosignal platforms. In this role, you will apply advanced machine learning, artificial intelligence, and signal-processing techniques to one of the world's largest labeled ECG datasets, with more than 10 million records, to develop innovative algorithms that can enhance diagnostic capabilities and ultimately improve patient outcomes.
Working at the intersection of machine learning, physiological signal processing, and digital health, you will explore complex bio signal data, develop and validate novel approaches to algorithmic interpretation, and help translate cutting-edge research into scalable solutions for real-world healthcare applications. You will also contribute to the development of next-generation algorithms for analyzing physiological signals generated by wearable and connected health technologies, helping expand how iRhythm transforms continuous health data into meaningful clinical insights.
Essential Duties and Responsibilities:- Design, develop, validate, and optimize machine learning algorithms for the analysis of biosignal data, including ECG and longitudinal health record data.
- Contribute to the development and evolution of the machine learning platform and infrastructure that powers iRhythm's diagnostic and insights capabilities.
- Partner with data scientists, software engineers, and clinical experts to translate research innovations into production-quality medical device algorithms.
- Communicate technical findings to cross-functional stakeholders, executive leadership, and external scientific audiences through publications and conference presentations.
Desired Experience and Qualifications: - MS or PhD in Computer Science, Electrical Engineering, Statistics or a related quantitative field.
- Work Experience: Proven track record working in machine learning, AI, image/signal processing or related field.
- Experience developing algorithms for safety-critical systems, preferably within regulated industries such as medical devices, healthcare, aerospace, automotive, or robotics.
Desired Knowledge, Skills and Abilities: - Deep expertise in machine learning, deep learning, statistical modeling, and time-series analysis.
- Experience with large-scale self-supervised learning, multimodal foundation models, representation learning, or generative AI techniques
- Experience developing and training modern deep learning architectures using frameworks such as PyTorch or TensorFlow.
- Strong programming skills in Python and familiarity with Python libraries such as numpy, scikit-learn, pandas, scipy, etc.
- Experience working with large data sets and knowledge of database languages such as SQL.
- Experience developing and deploying machine learning solutions on cloud platforms such as AWS, Azure, or GCP.
- Experience training large-scale deep learning models using distributed multi-node compute environments and optimizing performance at scale.
Location:Remote - US
Actual compensation may vary depending on job-related factors including knowledge, skills, experience, and work location.
Estimated Pay Range$187,000.00 - $243,000.00
