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Machine Learning Engineer, Cardiovascular Multi-Omics

Cardio Diagnostics Inc. · Chicago, IL

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About Cardio DiagnosticsCardio Diagnostics is a precision cardiovascular medicine company committed to making cardiovascular disease prevention and early detection more accessible, personalized, and precise. Our mission is to advance and commercialize our proprietary AI-driven multi-omics technology for cardiovascular disease, establishing ourselves as a leading medical technology company focused on improving prevention, diagnostics, and treatment in the field of cardiovascular health.The RoleWe are seeking a full-time, on-site Machine Learning Engineer to join Cardio Diagnostics. In this role, you will play a key part in developing our advanced platform and driving impactful machine learning initiatives across multiple disciplines, including operations, modeling, and data engineering. As a member of a small, agile team, you’ll take ownership of end-to-end machine learning projects. Responsibilities· Building and maintaining data pipelines for DNA methylation, genotype, and clinical data· Developing, validating, and maintaining machine learning models· Deploying and scaling machine learning models and data pipelines on cloud platforms such as AWS· Implementing MLOps practices on platforms such as MLflow, including model performance tracking, data and model drift detection, and feedback loops for continuous improvement· Maintaining code quality through coding standards, testing, peer code reviews, and version control· Collaborating with laboratory scientists, clinicians, and engineers to translate research into machine learning solutions· Documenting, summarizing, and presenting results to both technical and non-technical stakeholdersRequired Qualifications· MS with 2+ years of relevant industry experience, or PhD, in computer science, machine learning, statistics, computational biology, biomedical informatics, applied mathematics, or a related quantitative field· Self-directed, with a track record of quickly learning and applying new technologies and methods· Proficiency with machine learning libraries such as PyTorch and scikit-learn· Experience building, deploying, and maintaining machine learning systems in production· Experience with machine learning platforms such as MLflow· Ability to explain complex technical concepts clearly to technical and non-technical audiences· Strong Python skills, including writing production-quality codePreferred Qualifications