Job Description

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.