Senior MLOps Engineer – US East Coast Time Zone

🔥 4 hours ago

🐻 Alaska, Iowa, +6 more states – Remote

🐻 Alaska – Remote 🌾 Iowa – Remote 🌾 Nebraska – Remote 🎸 Mississippi – Remote 🗿 South Dakota – Remote ⚔️ Virginia – Remote ⛰️ West Virginia – Remote 🧀 Wisconsin – Remote

💵 $147.9k - $203k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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ŌURA

WebsiteLinkedInAll Job Openings

201 - 500 employees

🏥 Healthcare

🏭 Manufacturing

💼 Consulting

Healthcare • Manufacturing • Consulting

ŌURA is a company that produces smart rings designed to provide in-depth health metrics and insights. The Oura Ring tracks a variety of health-related data such as sleep patterns, heart rate, activity levels, and stress. It aims to help users live healthier and more productive lives through accurate biometrics tracked via a comfortable ring worn all day and night. With features that benefit women's health, heart health, and overall wellness, ŌURA rings are marketed as both technologically advanced and user-friendly devices for personal health monitoring.

📋 Description

• Lead the development and improvement of the environment, platform capabilities, and operational foundations supporting machine learning workflows across Oura • Drive the design and unification of workflows and tooling for reliable ML training, orchestration, and deployment • Partner with data scientists and engineers to improve the end-to-end ML lifecycle from experimentation and training through deployment and governance • Define and evolve model governance practices, including reproducibility, lineage, access controls, and operational standards • Standardize ML tooling and workflows such as experiment tracking, model packaging, and promotion processes • Collaborate across business domains to onboard use cases and prioritize shared ML platform improvements • Resolve reliability, scalability, and cost-efficiency issues in cloud ML infrastructure • Drive standards, automation, infrastructure-as-code, CI/CD, and documentation across data science teams • Improve observability and infrastructure automation for ML workflows • Contribute to workflow orchestration and platform integrations for model training and batch inference • Align ML systems with broader data platform and governance practices • Shape best practices for building, shipping, and maintaining production ML systems

🎯 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 • Strong understanding of cloud infrastructure concepts • Strong understanding of the machine learning lifecycle, including training workflows, deployment patterns, monitoring, and model maintenance • Familiarity with data science workflows and experimentation/model-operations tooling such as MLflow • 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 building or supporting production-grade ML workflows focused 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 in a distributed team with ownership and autonomy

🏖️ Benefits

• Competitive salary and equity packages • Health, dental, vision insurance, and mental health resources • An Oura Ring of your own plus employee discounts for friends & family • 20 days of paid time off plus 13 paid holidays plus 8 days of flexible wellness time off • Paid sick leave and parental leave