Platform Engineer
Core
Build a machine learning platform enabling the full lifecycle of deep learning models for cancer treatment planning, from data curation to production deployment.
Role type
Senior Machine Learning Platform Engineer (MLOps)
Builds
A robust model development platform serving ML engineers and product teams for clinical AI models
Domain
Healthcare technology / Medical imaging / MLOps
Deliverable
production ML models
Required skills
Python, backend services and APIs, relational databases (PostgreSQL), containers (Docker), CI/CD, observability, architecture design
Preferred skills
ML platforms and MLOps tooling (MLflow), PyTorch, inference optimization (TensorRT), workflow orchestration (Flyte, Airflow), Kubernetes, cloud infrastructure, medical imaging (DICOM)
Responsibilities
Design and build data curation pipelines for clinical datasets; orchestrate reproducible model training runs; implement automated validation and reporting tools; integrate models into production software; monitor and maintain platform services and databases
Seniority
Senior, hands-on IC