Staff Software Engineer, Machine Learning
$175k - $201k USD
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.
While we are mostly a remote company, travel is required for some team meetings and cross function projects typically once per month or once per quarter, for some roles like sales or external facing roles travel could be up to 90% of the time.
About the Opportunity
We are seeking an experienced Staff Machine Learning Engineer to architect, scale, and advance our machine learning platforms that bridge AI innovation and production in regulated healthcare. In this high-impact role, you will define and implement core platform capabilities, enabling scalable, secure, and compliant deployment of ML models that directly impact the care pathway for heart disease diagnosis and prognosis. You will tackle complex engineering challenges across end-to-end ML pipelines, ensuring reproducibility, efficiency, and compliance while driving the technical evolution of the platform.
About the Team
The AI Software Engineering team translates advanced ML models into production-ready, scalable solutions that directly impact the care pathway for heart disease diagnosis and prognosis. Working closely with AI scientists, software engineers, and regulatory teams, the team ensures models and ML workflows integrate seamlessly into clinical and product systems while maintaining reproducibility, compliance, and high performance. The team drives continuous improvements in efficiency, throughput, and infrastructure utilization, delivering reliable, scalable AI services that advance the accuracy and impact of Cleerly’s regulated products.
Responsibilities
- Architect and develop scalable AI/ML platforms and end-to-end pipelines, covering data ingestion, preprocessing, model training, evaluation, deployment, monitoring, drift detection, and automated retraining, while ensuring reproducibility, compliance with FDA/HIPAA, and alignment with organizational and regulatory goals.
- Optimize and operationalize production ML systems, including monitoring, drift detection, automated retraining, and workflow execution, to achieve high performance, reliability, scalability, and regulatory adherence.
- Evolve the ML stack through integration and refinement of frameworks, libraries, and infrastructure, improving system efficiency, maintainability, and the ability to support clinical ML workflows.
- Ensure operational readiness of ML pipelines and platforms, verifying data quality, throughput, reproducibility, and compliance across production workflows.
- Drive improvements in processes, tooling, and collaboration to streamline the transition of ML models from research to production, enhancing efficiency, reproducibility, and compliance across the platform.
Requirements
- 12+ years of experience (Bachelor’s; 8+ with Master’s; 5+ with PhD) designing, implementing, and optimizing AI and ML systems, ideally in regulated healthcare or clinical domains.
- Deep technical expertise in ML pipelines, distributed model serving architectures, and production ML lifecycle management, with a track record of solving high-impact system challenges.
- Proficiency in Python, Java, or similar, with extensive programming experience establishing reproducible ML workflows, coding standards, and software engineering best practices for AI/ML applications.
- Proficiency with ML infrastructure and orchestration tools (Kubernetes, Helm, Airflow) and data platforms (Snowflake, PostgreSQL, Airbyte), and building scalable pipelines that support ML data processing and model workflows.
- Advanced experience with AWS (including SageMaker and S3), ML infrastructure frameworks such as MLflow and Terraform, and exposure to platforms like Databricks, with a proven track record of implementing end-to-end ML systems and optimizing platform performance, scalability, and operational efficiency.
- Proven ability to influence technical approaches and operational practices in AI/ML workflows, elevating system efficiency, reproducibility, and reliability.
- Strong expertise in regulatory and compliance requirements for AI/ML (FDA, HIPAA), able to design systems that are inherently compliant, reproducible, and auditable. (Preferred)
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: $175,000 - $201,000
- TTC: $200,000 - $231,000
*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.
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