27 days ago
Base Salary
$148k - $203k/yr
Responsibilities
- Lead the development and improvement of shared platforms and operational foundations for machine learning workflows.
- Design and standardize workflows for ML training, orchestration, deployment, experiment tracking, model packaging, and promotion.
- Partner with data scientists and engineers to improve the end-to-end ML lifecycle and production system maintainability.
- Define model governance practices covering reproducibility, lineage, access controls, and operational standards.
- Identify and resolve reliability, scalability, and cost-efficiency issues in cloud-based ML infrastructure.
- Drive infrastructure automation, infrastructure-as-code, CI/CD, observability, documentation, and workflow standardization across teams.
- Collaborate with data engineering and platform teams to support model training, batch inference, governance, and platform integrations.
Requirements
- 5+ years of experience in MLOps, machine learning engineering, platform engineering, data engineering, or a closely related field.
- Hands-on experience running production workloads in AWS and a strong understanding of cloud infrastructure concepts.
- Strong understanding of ML training workflows, deployment patterns, monitoring, and ongoing model maintenance.
- Familiarity with MLflow or similar tooling for experimentation and model operations.
- Familiarity with workflow orchestration, infrastructure-as-code, and CI/CD practices for ML or data platforms.
- Familiarity with secure access patterns, governance controls, and shared cloud or data platform services.
- Experience supporting production-grade ML workflows with an emphasis on reliability, reproducibility, and maintainability.
- Ability to drive standards and improvements across multiple teams and business domains.
- Strong communication and collaboration skills with technical and non-technical stakeholders.
- Ability to operate with ownership and autonomy in a distributed team.
- Preferred experience supporting multiple data science teams through shared MLOps platforms or tooling.
- Prior experience with Databricks and ML governance or operational controls at scale is preferred.
- Experience driving cross-team tooling or workflow standardization in ML or data platforms is preferred.
Benefits
- Competitive salary and equity packages.
- Health, dental, vision insurance, and mental health resources.
- An Oura Ring plus employee discounts for friends and family.
- 20 days of paid time off, 13 paid holidays, and 8 days of flexible wellness time off.
- Paid sick leave and parental leave.
- Remote role in the US; candidates residing in Alaska, Delaware, Iowa, Mississippi, Nebraska, South Dakota, West Virginia, and Wisconsin are not considered.
Tech Stack
Categories
About Ōura
Ōura makes the Oura Ring—a finger-worn health wearable—and companion app that track sleep, activity, and physiological signals; it sells devices directly to consumers and offers a paid membership for advanced insights. Founded in 2013 and headquartered in San Francisco, the company is privately held. Its service runs on iOS and Android and is used by consumers worldwide.