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CertifyCE

AI/ML Intern

CertifyOS is an innovative provider intelligence platform that streamlines healthcare operations via an API-driven approach to credentialing, licensing, and monitoring.

Certify

Employee count: 51-200

India only

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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 like never before. With direct integrations into hundreds of primary sources, we have an unbeatable advantage in enhancing visibility into the entire provider network management process. Plus, our team brings over 25+ years of combined experience building provider data systems at Oscar Health, and we're backed by top-tier VC firms who share our bold vision of creating a one-of-a-kind healthcare cloud that eliminates friction surrounding provider data.
But it's not just about the technology; it's about the people behind it. At Certify, we foster a meritocratic environment where every voice is heard, valued, and celebrated. We're founded on the principles of trust, transparency, and accountability, and we're not afraid to challenge the status quo at every turn. We're looking for purpose-driven individuals like you to join us on this exhilarating ride as we redefine healthcare data infrastructure.

About The Role:

  • We’re looking for an independently-motivated Machine Learning Engineer for a 6-month contract to help us build, test, and deploy ML-powered services on our provider data platform.
  • This is not a pure research or model-tweaking role. We care more about strong software engineering, testing, and robust evaluation than novel model architectures. You’ll own features end-to-end: collaborating with stakeholders, implementing production-ready code, designing evaluation pipelines, and deploying services on Google Cloud Platform (GCP).
  • If you enjoy building reliable ML systems, talking to internal users, learning about the holistic business side of AI in production, and making sure what you ship actually works in the real world, this role is for you.

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, heavily using but not relying upon best practices in prompt engineering.
  • 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 rather than just model accuracy.
  • Proactively engage with internal stakeholders (product, operations, engineering, data) to clarify requirements and iterate on solutions.
  • Communicate clearly about trade-offs, risks, timelines, and results to both 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 (also in English).
  • Comfort proactively reaching out to internal stakeholders to understand needs instead of waiting for perfectly written specs.

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).
At Certify, we're committed to creating an inclusive workplace where everyone feels valued and supported. As an equal opportunity employer, we celebrate diversity and warmly invite applicants from all backgrounds to join our vibrant community.

About the job

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Posted on

Job type

Intern

Experience level

Entry-level

Location requirements

Hiring timezones

India +/- 0 hours

About Certify

Learn more about Certify and their company culture.

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CertifyOS is a pioneering provider intelligence platform dedicated to redefining the way healthcare organizations manage provider data. Founded in 2020, CertifyOS leverages advanced technology to provide frictionless credentialing, licensing, enrollment, and network monitoring for healthcare providers. The platform is designed with an API-first approach, aiming to streamline and modernize the complexities surrounding provider data management. By automating these processes, CertifyOS significantly reduces the administrative burdens faced by health systems, thereby promoting efficiency and accuracy in provider data management.

At CertifyOS, our mission goes beyond merely enhancing operations; we strive to improve patient care by ensuring that provider data is accurate, readily accessible, and actionable. With a robust team that has over 75 years of combined experience in healthcare data systems, we have developed a platform powered by hundreds of verified data points and direct integrations with various primary data sources. This allows healthcare organizations to verify provider data in real time and maintain compliance effortlessly, all while reducing costs associated with manual workflows. Our vision is to create a single source of truth for provider data, facilitating informed decision-making and improved patient outcomes.

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