About Certify
At CertifyOS, we're building the infrastructure that powers the next generation of provider data products, making healthcare more efficient, accessible, and innovative. Our platform is the ultimate source of truth for provider data, offering unparalleled ease and trust while making data easily accessible and actionable for the entire healthcare ecosystem.
What sets us apart? Our cutting-edge, API-first, UI-agnostic, end-to-end provider network management platform automates licensing, enrollment, credentialing, and network monitoring. With direct integrations into hundreds of primary sources, we enhance visibility across the provider network management process. Our team brings 25+ years of combined experience building provider data systems and we're backed by top-tier VCs to build a healthcare cloud that eliminates friction surrounding provider data.
About The Role
We’re looking for an independently-motivated Machine Learning Engineer for a 6-month contract to help build, test, and deploy ML-powered services on our provider data platform. This is a production-focused role: strong software engineering, testing, and robust evaluation are prioritized over pure research or novel model architectures. You will own features end-to-end, collaborating with stakeholders, implementing production-ready code, designing evaluation pipelines, and deploying services on Google Cloud Platform (GCP).
What you will do
- Design, implement, and maintain ML-driven services and data workflows in Python.
- Apply software engineering best practices: clean code, testing (unit/integration), code review, CI/CD, observability, and documentation, using prompt engineering best practices where appropriate.
- Build and maintain evaluation pipelines and metrics to measure model and system performance in production-like environments.
- Deploy and operate ML services on GCP (for example Cloud Run, GKE, Cloud Functions, Pub/Sub, BigQuery, Cloud Storage).
- Troubleshoot and improve existing ML services, focusing on reliability, latency, and correctness.
- Engage proactively with internal stakeholders (product, operations, engineering, data) to clarify requirements and iterate on solutions.
- Communicate clearly about trade-offs, risks, timelines, and results to technical and non-technical audiences.
What you will need
- Experience as a Software Engineer or ML Engineer.
- Strong proficiency in Python and experience building production services.
- Hands-on experience deploying and running workloads on GCP (e.g., Cloud Run, GKE, Cloud Functions, BigQuery, Pub/Sub).
- Expertise in writing and debugging SQL queries.
- Demonstrated strength in software engineering fundamentals: testing, debugging, version control (Git), CI/CD, and monitoring.
- Experience with evaluating ML systems: defining metrics, building evaluation datasets, running experiments, and interpreting results.
- Ability to work independently, take ownership, and drive projects with limited supervision.
- Excellent written and verbal communication skills (including English).
- Comfort proactively reaching out to internal stakeholders to understand needs.
Bonus points if you
- Have experience writing code in Java.
- Have built or maintained data pipelines/ETL jobs on GCP.
- Have experience with healthcare data, compliance, or working with PII.
- Have used experiment tracking and evaluation tools (e.g., MLflow, Weights & Biases, custom dashboards).
Certify is committed to creating an inclusive workplace and is an equal opportunity employer. We welcome applicants from all backgrounds.
How to Apply
To apply, click the "Apply for this job" link on the job posting page or visit the application URL: https://jobs.lever.co/certifyos/a5c92edf-ffea-4858-905e-dfe70deba443/apply