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$147,900 – $203,000
Listed on Oura’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
This role leads the design and operation of machine learning platforms that enable data science teams to reliably develop, train, and deploy models at scale. It suits experienced engineers who thrive working across multiple teams to build infrastructure, standardize workflows, and improve ML systems in a growing company.
Our summary, not Oura’s wording. The full posting is on their site.
Skills this role names
- Amazon Web Services (AWS)
- Apache Airflow
- CI/CD
- Databricks
- Infrastructure as Code
- Kubernetes
- MLflow
- Python
- Terraform
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What they ask for
Required
- 5+ years in MLOps, machine learning engineering, platform engineering, or data engineering
- Production workload experience in AWS
- Understanding of machine learning lifecycle including training, deployment, monitoring, and model maintenance
- Familiarity with MLflow or similar experiment tracking tools
- Experience with workflow orchestration and infrastructure-as-code
- Knowledge of governance controls and secure access patterns for ML systems
- Production-grade ML workflows with focus on reliability and reproducibility
- Ability to drive standards across multiple teams
- Strong communication and collaboration skills
- Autonomy and ownership in distributed team environments
Nice to have
- Experience supporting multiple data science teams through shared MLOps platforms
- Prior Databricks experience
- Governance and operational controls for ML systems at scale
- Cross-team tooling or workflow standardization in ML or data platforms
- Background in high-growth environments with evolving ML platform needs