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CertifyOS - AI Intern

CertifyOS의 의료 제공자 데이터 플랫폼에서 ML 기반 서비스를 구축·테스트·배포하는 6개월 계약 인턴(ML 엔지니어) 역할입니다. Python으로 ML 서비스와 데이터 워크플로우를 개발하고, GCP(Cloud Run, GKE, Pub/Sub, BigQuery 등)에 배포하며, 평가 파이프라인과 메트릭을 설계해 프로덕션 성능을 측정합니다. 연구보다 소프트웨어 엔지니어링·테스트·평가에 강점을 둔, 프로덕션 경험이 있는 ML/소프트웨어 엔지니어에게 적합합니다.

2026.07.29VIEW 14RemoteOK에서 수집
Budget협의
Difficulty고급
Duration6개월
Work style원격 가능
Required stack

필요 기술

PythonGCPBigQuerySQLCloud RunGKEPub/SubGit
Project brief

프로젝트 내용

About CertifyOS
CertifyOS is building the data infrastructure that powers modern healthcare.
Today, healthcare organizations rely on fragmented and outdated provider data. This creates unnecessary administrative work, regulatory risk, and higher costs across the system. We’re solving that problem.
Our API-first platform automates provider licensing, enrollment, credentialing, and network monitoring by connecting directly to hundreds of primary data sources. We help healthcare organizations maintain accurate, compliant, and reliable provider networks at scale.
Our vision is simple: One API. One provider ID. Frictionless provider data.
We’re backed by leading investors and built by a team with deep experience in provider data systems. At CertifyOS, we value authenticity, accountability, collaboration, results, and openness to feedback. We’re building a high-ownership team focused on solving real infrastructure problems that impact millions of patients.

About the Role:
As an Intern Machine Learning Engineer on a 6-month contract, you will help build, test, and deploy ML-powered services on our provider data platform. This is not a pure research role; the focus is on strong software engineering, testing, and robust evaluation rather than novel model architectures.
You will own features end-to-end by collaborating with stakeholders, implementing production-ready code, designing evaluation pipelines, and deploying services on Google Cloud Platform (GCP). This is a fully remote position.
What You’ll Do:
Design, implement, and maintain ML-driven services and data workflows in Python.
Apply software engineering best practices, including clean code, testing (unit and integration), code reviews, CI/CD, observability, and documentation.
Build and maintain evaluation pipelines and metrics to measure model and system performance in production-like environments.
Deploy and operate ML services on GCP, including tools such as Cloud Run, GKE, Cloud Functions, Pub/Sub, BigQuery, and Cloud Storage.
Troubleshoot and improve existing ML services with a focus on reliability, latency, and correctness.
Collaborate proactively with internal stakeholders across product, operations, engineering, and data teams 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’ll Need:
Experience as a Software Engineer or Machine Learning Engineer.
Strong proficiency in Python and experience building production services.
Hands-on experience deploying and running workloads on Google Cloud Platform.
Expertise in writing and debugging SQL queries.
Strong foundation in software engineering fundamentals, including testing, debugging, version control (Git), CI/CD, and monitoring.
Experience evaluating ML systems by 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 in English.
Comfort proactively reaching out to internal stakeholders to understand requirements.
Bonus Points If You:
Have experience writing code in Java.
Have built or maintained data pipelines or ETL jobs on GCP.
Have experience working with healthcare data, compliance requirements, or PII.
Have used experiment tracking and evaluation tools such as MLflow, Weights & Biases, or custom dashboards.
 

Benefits of Working at Certify
- At Certify, we’re building with intention and taking care of the people doing the work.

- Your well-being matters to us. We provide 100% coverage of health, dental, and vision insurance premiums for employees. Our US-based team benefits from unlimited PTO, with at least two weeks off each year to recharge. In India, employees are supported with health insurance, statutory leave benefits, and additional wellness (menstrual) leave for women.

We are an equal opportunity employer committed to building an inclusive environment where everyone feels valued and empowered to do their best work, and we welcome applicants from all backgrounds and experiences.
If you require reasonable accommodations during the application process, please contact recruiting@certifyos.com.
We are also committed to pay transparency and foster an open culture where compensation conversations are encouraged and respected.

Please mention the word **PEACEFUL** and tag RMTUuMTY1LjI0MC4xNDk= when applying to show you read the job post completely (#RMTUuMTY1LjI0MC4xNDk=). This is a beta feature to avoid spam applicants. Companies can search these words to find applicants that read this and see they're human.
지원 기회 분석

지원 전에 볼 것

핵심 요구사항

  • Python 프로덕션 서비스 개발 능력
  • GCP 워크로드 배포·운영 경험
  • SQL 작성 및 디버깅 역량
  • 테스트·CI/CD·모니터링 등 SW 엔지니어링 기본기
  • ML 시스템 평가(메트릭 정의·실험·해석) 경험
  • 독립적으로 프로젝트를 주도하는 오너십

예상 산출물

  • 프로덕션 수준의 ML 서비스 및 데이터 워크플로우
  • 모델·시스템 성능 평가 파이프라인 및 메트릭
  • GCP에 배포·운영되는 ML 서비스
  • 테스트·문서화·CI/CD 구성

매력 포인트

  • 명확하고 상세한 업무 스펙
  • 최신 GCP·MLOps 스택 경험 기회
  • 투자 유치된 헬스케어 인프라 기업

확인할 점

  • 인턴 직무임에도 실무 프로덕션 경험을 다수 요구
  • 예산·급여 정보 미공개
Client signal

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