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 machine learning 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
- Collaborate with AI scientists to package and deploy ML models, ensuring reproducibility, versioning, and compliance.
- Build and maintain model serving infrastructure including monitoring, drift detection, automated retraining, and logging.
- Implement unit, integration, and system-level testing for ML models, covering data validation, model correctness, and deployment workflows.
- Develop and operate end-to-end ML pipelines: ingestion → preprocessing → feature engineering → evaluation → deployment → monitoring.
- Integrate CI/CD and MLOps practices for automated model builds, testing, and deployment.
- Identify and resolve workflow inefficiencies or gaps between research and production.
- Recommend and integrate frameworks, libraries, and infrastructure to improve pipeline efficiency, maintainability, and observability.
- Collaborate cross-functionally to ensure compliance with regulatory requirements (FDA/HIPAA) in production ML workflows.
- 7+ years of experience in software engineering for ML production or ML platform delivery.
- Hands-on experience deploying ML models via APIs, batch pipelines, or streaming inference.
- Proficiency in Python (required), Java, or similar, with software engineering best practices for ML workflows.
- Experience with unit, integration, and pipeline-level testing for ML models, including data validation, correctness checks, and reproducibility.
- Familiarity with cloud platforms (AWS preferred: SageMaker, S3, EC2) and reproducible ML pipelines.
- Experience with CI/CD, Orchestration tools (Airflow, MLflow, Kubernetes, Terraform) and ML/data platforms(SageMaker, Databricks, Unity Catalog, Snowflake/Snowpark) to build scalable ML data pipelines and model workflows.
- Strong collaboration skills to work effectively with AI scientists, software engineers, and regulatory teams.
The base salary range for this role varies by location and is aligned to market benchmarks.
- Candidates located in higher-cost labor markets, including California, Washington, New York, New Jersey, Connecticut, Massachusetts, and Washington, DC represent the middle to high end of the range, while candidates located in all other U.S. locations represent the low to middle end of the range.
- Final compensation is determined based on location, experience, skills, and internal equity.
This role is eligible for a 15% target annual bonus, resulting in the following base salary and Total Target Compensation (TTC) ranges:
- Base Salary: $153,000 - $179,000
- TTC: $176,000 - $206,000
*Total Target Compensation (TTC): Total Cash Compensation (including base pay, variable pay, commission, bonuses, etc.) Additionally, stock options, paid benefits, and employee perks are part of your total rewards.
Working at Cleerly takes HEART. Discover our Core Values:
- H: Humility- be a servant leader
- E: Excellence- deliver world-changing results
- A: Accountability- do what you say; expect the same from others
- R: Remarkable- inspire & innovate with impact
- T: Teamwork- together we win
Don’t meet 100 percent of the qualifications? Apply anyway and help us diversify our candidate pool and workforce. We value experience, whether gained formally or informally on the job or through other experiences. Job duties, activities and responsibilities are subject to change by our company.
OUR COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER. We do not discriminate on the basis of race, color, national origin, ancestry, citizenship status, protected veteran status, religion, physical or mental disability, marital status, sex, sexual orientation, gender identity or expression, age, or any other basis protected by law, ordinance, or regulation.
For more information see our Privacy Policy (https://cleerlyhealth.com/privacy-policy). All official emails will come from @cleerlyhealth.com email accounts.
#Cleerly
Skills Required
- 7+ years of experience in software engineering for ML production or ML platform delivery
- Hands-on experience deploying ML models via APIs, batch pipelines, or streaming inference
- Proficiency in Python (required), Java, or similar
- Experience with unit, integration, and pipeline-level testing for ML models
- Familiarity with cloud platforms (AWS preferred) and reproducible ML pipelines
- Experience with CI/CD, Orchestration tools, and ML/data platforms
What We Do
Cleerly is creating 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.
Why Work With Us
We’re Cleerly – a healthcare company based in Denver, Colorado and New York, New York 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.
