About Cardio Diagnostics Cardio 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.
We 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.
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 stakeholders
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
· Proficiency with machine learning libraries such as scikit-learn
· Experience building, deploying, and maintaining machine learning systems in production
· Experience with machine learning platforms such as MLflow
· Strong Python skills, including writing production-quality code
Experience with DNA methylation, genomic, or other multi-omic data
• Experience applying machine learning to cardiovascular disease
• Experience with large-scale data processing tools such as Apache Spark, Databricks, or AWS EMR
• Peer-reviewed publications in machine learning, computational biology, or a related field
Salary-only position with no bonus component
• Comprehensive medical, dental, and vision coverage
• Schedule: 4 days in office and 1 remote day each week
• 5 additional remote days every 6 months
• Cardio Diagnostics does not provide H-1B sponsorship at this time
We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
We 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.
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 stakeholders
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
· Proficiency with machine learning libraries such as scikit-learn
· Experience building, deploying, and maintaining machine learning systems in production
· Experience with machine learning platforms such as MLflow
· Strong Python skills, including writing production-quality code
Experience with DNA methylation, genomic, or other multi-omic data
• Experience applying machine learning to cardiovascular disease
• Experience with large-scale data processing tools such as Apache Spark, Databricks, or AWS EMR
• Peer-reviewed publications in machine learning, computational biology, or a related field
Salary-only position with no bonus component
• Comprehensive medical, dental, and vision coverage
• Schedule: 4 days in office and 1 remote day each week
• 5 additional remote days every 6 months
• Cardio Diagnostics does not provide H-1B sponsorship at this time
We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other characteristic protected by law.
Machine Learning Engineer, Cardiovascular Multi-Omics in chicago at Unknown Company
This position is listed as full time and able to be worked remotely.