Sr. Software Engineer - ML Systems
CleerlyAbout the role
About Cleerly
We’re Cleerly – a healthcare company that’s revolutionizing how heart disease is diagnosed, treated, and tracked. We were founded in 2017 by one of the world’s leading cardiologists and are a growing team of world-class engineering, operations, medical affairs, marketing, and sales leaders. We raised $223M in Series C funding in 2022 which has enabled rapid growth and continued support of our mission. In December 2024 we received an additional $106M in a Series C extension funding. Most of our teams work remotely and have access to our offices in Denver, Colorado, New, York, New York, Dallas, Texas, and Lisbon, Portugal with some roles requiring you to be on-site in a location.
Cleerly has created a new standard of care for heart disease through value-based, AI-driven precision diagnostic solutions with the goal of helping prevent heart attacks. Our technology goes beyond traditional measures of heart disease by enabling comprehensive quantification and characterization of atherosclerosis, or plaque buildup, in each of the heart arteries. Cleerly’s solutions are supported by more than a decade of performing some of the world’s largest clinical trials to identify important findings beyond symptoms that increase a person’s risk of heart attacks.
At Cleerly, we collaborate digitally and use a wide variety of systems. Our people use Google Workspace (GMail, Drive, Docs, Sheets, Slides), Slack, Confluence/Jira, and Zoom Video, prior experience in these areas is a plus. Role or department specific technology needs may vary and will be listed as requirements in the job description.
About the Opportunity
We are seeking a Senior Software Engineer to design, build, deploy, monitor, and optimize production-ready ML services in regulated healthcare. You will work hands-on to package, test, orchestrate, deploy, and maintain ML models, improve workflows, and implement CI/CD and automated testing to ensure reliability, performance, and faster delivery of business value.
Responsibilities
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Design, build, and deploy scalable AI/ML services with clear service boundaries, making pragmatic trade-offs across performance, maintainability, security, and long-term extensibility.
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Own full lifecycle delivery of complex features from architectural planning and API design to implementation and post-release observability.
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Define and enforce robust verification and validation for AI services including unit, integration, and end-to-end testing to ensure reliability of code in production and compliance with our Quality Management System and regulatory standards.
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Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.
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Translate product requirements into well-defined technical designs proactively shaping implementation details.
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Contribute to the necessary technical documentation required for regulatory submissions.
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Collaborate cross functionally to reduce knowledge silos and ensure continuity in critical systems through cross-training and documentation.
Requirements
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Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field
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7+ years of software engineering experience, with expertise in AI production systems (Python, PyTorch) and data services (SQL, Postgres, NoSQL, Redis or similar).
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Experience with unit, integration testing for ML models, including data validation, correctness checks, and reproducibility.
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Experience with CI/C
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