A strong Python engineer comfortable across production services and machine learning. The codebase is predominantly Python — microservices with ML components running on AWS. A build-and-maintain role on a live, regulated healthcare product: production-grade engineering discipline is expected, not research-only work.
What you'll do
- Build and maintain Python microservices (FastAPI) deployed on AWS (ECS, Fargate)
- Work with ML models and pipelines, including managed training and inference (SageMaker)
- Integrate cloud services — SQS for events, API Gateway for traffic, secure service-to-service auth
- Ship production-grade, well-tested code within full CD pipelines (development, staging, production)
- Contribute to CI quality gates — automated testing, build verification and code review
- Collaborate with architecture, frontend and data colleagues in a distributed team
Must have
- Strong production Python — real services and APIs, not notebooks only
- FastAPI or an equivalent framework, and containerised deployment (Docker)
- Hands-on AWS — ideally ECS / Fargate, SQS, API Gateway
- Experience shipping code through CI/CD pipelines with automated testing
- Professional English, verbal and written
Nice to have
- ML / SageMaker experience (training and deploying models in production)
- Healthcare or clinical-data experience (HL7 / FHIR, EHR integration)
- Terraform / Infrastructure as Code familiarity
- Event-driven / microservice architecture experience
Apply for this role
Or email your CV to careers@luminovalabs.net and include the reference ML04 in the subject.