Machine Learning Scientist

iRhythm Technologies, Inc.

. Design, develop, validate, and optimize machine learning algorithms for biosignal data, including ECG and longitudinal health record data.

Posted 10/6/2026full-timeRemote • United StatesMid-LevelSenior💰 $187,000 - $243,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in machine learning and deep learning for biosignal data analysis, with a strong focus on developing algorithms for medical devices and healthcare applications. Proficient in translating complex research into scalable solutions while effectively communicating findings to diverse stakeholders.

Highest-signal resume keywords

Machine LearningDeep LearningAlgorithm DevelopmentPython ProgrammingCloud Platforms

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningStatistical ModelingTime-Series AnalysisSignal ProcessingAlgorithm DevelopmentSelf-Supervised LearningGenerative AI TechniquesLarge-Scale Data ProcessingDatabase Languages

Soft Skills

CommunicationCollaborationProblem-Solving

Tools & Technologies

PyTorchTensorFlowAWSAzureGCPNumpyScikit-LearnPandasScipySQL

Industry Keywords

Medical DevicesHealthcareRegulated IndustriesSafety-Critical SystemsBiosignal Data

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformNode.jsNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Design, develop, validate, and optimize machine learning algorithms for biosignal data, including ECG and longitudinal health record data.
Contribute to the development and evolution of the machine learning platform and infrastructure powering 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.
Apply machine learning, artificial intelligence, and signal-processing techniques to a large labeled ECG dataset to develop algorithms that enhance diagnostic capabilities and patient outcomes.
Explore complex biosignal data, develop and validate novel algorithmic interpretation approaches, and translate research into scalable healthcare solutions.
Contribute to next-generation algorithms for analyzing physiological signals from wearable and connected health technologies.

Requirements

What you’ll need

MS or PhD in Computer Science, Electrical Engineering, Statistics or a related quantitative field.
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.
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 numpy, scikit-learn, pandas, scipy, and related libraries.
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.