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Software Development

Senior MLOps Engineer

ŌURA · United States · full-time · Remote

Software Developmentfull-timeRemoteUnited StatesUSD 147,900 – 203,000 / yearly
Data Science & AnalyticsSenior
RemoteJobs editorial overview

Strategic Overview

Senior MLOps Engineer at ŌURA is defined by the responsibilities and candidate requirements in the employer's listing.

The published role emphasizes work such as Lead the development and improvement of the environment, platform capabilities, and operational foundations that support machine learning workflows across Oura.

The role is listed for United States with a remote working arrangement, giving candidates the practical context needed to assess fit before applying.

Job seeker snapshot

Key information at a glance

Role focusSoftware Development
LocationUnited States
WorkplaceRemote
Employmentfull-time
SalaryUSD 147,900 – 203,000 / yearly
PostedNov 1, 2026
Last seenNov 2, 2026
Role context

About This Role

Our mission at ŌURA is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are looking for a Senior MLOps Engineer to join our Data Engineering & Analytics team.

What the role delivers

Key Responsibilities & Objectives

  • Lead the development and improvement of the environment, platform capabilities, and operational foundations that support machine learning workflows across Oura.
  • Drive the design and unification of workflows and tooling that support reliable training, orchestration, and deployment of ML systems.
  • Partner with data scientists and engineers to improve the end-to-end ML lifecycle, from experimentation and training through deployment and governance, while making production ML systems easier to manage and maintain.
  • Define and evolve model governance practices, including reproducibility, lineage, access controls, and operational standards.
  • Support and help standardize ML tooling and workflows such as experiment tracking, model packaging, and promotion processes, with MLflow or similar tooling as a key part of the stack.
  • Collaborate with teams across multiple business domains to onboard new use cases, prioritize platform improvements, and raise the maturity of shared ML capabilities.
  • Drive standards, automation, infrastructure-as-code, CI/CD, and documentation that make ML development easier and more consistent across multiple DS teams.
  • Improve infrastructure automation, CI/CD, and observability for ML workflows and supporting platform components.
  • Contribute to workflow orchestration and platform integrations that support model training and batch inference at scale.
  • Partner with data engineering and platform teams to align ML systems with broader data platform and governance practices.
Candidate blueprint

Required Qualifications & Candidate Blueprint

  • 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 the machine learning lifecycle, including training workflows, deployment patterns across ML systems, monitoring, and ongoing model maintenance.
  • Familiarity with data science ways of working and the tooling that supports experimentation and model operations, 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 that support ML work at scale.
  • Proven ability to drive standards and improvements across multiple teams and business domains.
  • Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
  • Comfort operating in a distributed team with a high degree of ownership and autonomy.
  • Prior experience with Databricks.
Compensation & benefits

Salary & Benefits

Published compensation: USD 147,900 – 203,000 / yearly

  • 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
  • Region 1 $172,550 - $203,000
Employer-provided source content

Full Job Description

The following is the complete job description supplied by the source. We sanitize unsafe markup and remove external links, but do not shorten or rewrite the employer's source content.

Our mission at ŌURA is to empower every person to own their inner potential. Our award-winning products help our global community gain a deeper knowledge of their readiness, activity, and sleep quality by using their Oura Ring and its connected app. We've helped millions of people understand and improve their health by providing daily insights and practical steps to inspire healthy lifestyles.

Empowering the world starts with living our values and empowering our team. As a quickly growing company focused on helping people live healthier and happier lives, we ensure that our team members have what they need to do their best work — both in and out of the office.

We are looking for a Senior MLOps Engineer to join our Data Engineering & Analytics team.

In this role, your primary focus will be leading the design and evolution of the platforms, workflows, and governance practices that enable machine learning teams to develop, train, deploy, and operate ML systems reliably at scale. You will work across multiple data science teams and business domains, shaping a strong development environment, driving model lifecycle improvements, and helping set the standards that keep our ML systems scalable, maintainable, and well governed. The role sits within a broader shared cloud and data platform ecosystem, so you will also collaborate with adjacent platform teams and contribute to practical infrastructure, deployment, and access patterns that help DS teams move faster.

This is a remote role in the US.

What you will do:

Primary Focus – MLOps Platform and ML Enablement

  • Lead the development and improvement of the environment, platform capabilities, and operational foundations that support machine learning workflows across Oura.
  • Drive the design and unification of workflows and tooling that support reliable training, orchestration, and deployment of ML systems.
  • Partner with data scientists and engineers to improve the end-to-end ML lifecycle, from experimentation and training through deployment and governance, while making production ML systems easier to manage and maintain.
  • Define and evolve model governance practices, including reproducibility, lineage, access controls, and operational standards.
  • Support and help standardize ML tooling and workflows such as experiment tracking, model packaging, and promotion processes, with MLflow or similar tooling as a key part of the stack.
  • Collaborate with teams across multiple business domains to onboard new use cases, prioritize platform improvements, and raise the maturity of shared ML capabilities.
  • Identify and resolve reliability, scalability, and cost-efficiency issues in ML infrastructure running in the cloud.
  • Drive standards, automation, infrastructure-as-code, CI/CD, and documentation that make ML development easier and more consistent across multiple DS teams.

Cross-functional Growth Areas

  • Improve infrastructure automation, CI/CD, and observability for ML workflows and supporting platform components.
  • Contribute to workflow orchestration and platform integrations that support model training and batch inference at scale.
  • Partner with data engineering and platform teams to align ML systems with broader data platform and governance practices.
  • Help shape best practices for how teams build, ship, and maintain production ML systems across Oura.

We would love to have you on our team if you have

  • 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 the machine learning lifecycle, including training workflows, deployment patterns across ML systems, monitoring, and ongoing model maintenance.
  • Familiarity with data science ways of working and the tooling that supports experimentation and model operations, 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 that support ML work at scale.
  • Experience building or supporting production-grade ML workflows with a focus on reliability, reproducibility, and maintainability.
  • Proven ability to drive standards and improvements across multiple teams and business domains.
  • Strong communication and collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.
  • Comfort operating in a distributed team with a high degree of ownership and autonomy.

What makes you stand out

  • Experience supporting multiple data science teams through shared MLOps platforms or tooling.
  • Prior experience with Databricks.
  • Experience with governance and operational controls for ML systems at scale.
  • Experience driving cross-team tooling or workflow standardization in ML or data platforms.
  • Experience working in a high-growth environment with multiple stakeholders and evolving ML platform needs.

Benefits

At Oura, we care about you and your well-being. Everyone here at Oura has a ring of their own and we are continually looking to improve employee health.

What we offer:

  • 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

Oura takes a market-based approach to pay, which may vary depending on your location. US locations are categorized into tiers based on a cost of labor index for that geographic area. While most offers will be closer to the starting range, successful candidates' pay will be determined based on job-related skills, experience, qualifications, work location, internal peer equity, and market conditions. These ranges may be modified in the future.

  • Region 1 $172,550 - $203,000
  • Region 2 $158,950 - $187,000
  • Region 3 $147,900 - $174,000

A recruiter can determine your zones/tiers based on your US location.

We are not considering candidates residing in the following states: Alaska (AK), Delaware (DE), Iowa (IA), Mississippi (MS), Nebraska (NE), South Dakota (SD), West Virginia (WV), and Wisconsin (WI)

ŌURA is proud to be an equal opportunity workplace. We celebrate diversity and are committed to creating an inclusive environment for all employees. Individuals seeking employment at ŌURA are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), gender identity or expression, genetic information, marital status, medical condition, mental or physical disability, national origin, protected family care or medical leave status, race, religion (including beliefs and practices or the absence thereof), sexual orientation, military or veteran status, or any other characteristic protected by federal, state, or local laws. We will not tolerate discrimination or harassment based on any of these characteristics.

We will work to ensure individuals with disabilities are provided reasonable accommodation to participate in the interview process, to perform essential job functions, and to receive other benefits and privileges of employment.

Disclaimer: Beware of fake job offers!
We’ve been alerted to scammers posing as ŌURA recruiters, especially for remote roles. Please note:

  • Our jobs are listed only on the ŌURA Careers page and trusted job boards.
  • We will never ask for personal information like ID or payment for equipment upfront.
  • Official offers are sent through Docusign after a verbal offer, not via text or email.

Stay cautious and protect your personal details.

To all recruitment agencies: ŌURA does not accept agency resumes. Please do not forward resumes to our jobs alias, ŌURA employees, or any other organization's location. ŌURA is not responsible for any fees related to unsolicited resumes.

RemoteJobs original analysis

Editor’s Market Perspective (Our Custom Analysis)

Why This Position Matters

This opening may suit candidates who can demonstrate experience relevant to the employer's published requirements. Its strongest career signal is the scope of the work itself — particularly Lead the development and improvement of the environment, platform capabilities, and operational foundations that support machine learning workflows across Oura. — rather than a generic title alone.

Resume & Application Strategy

For the application, connect specific examples from your experience to the responsibilities and qualifications in the employer's description. Quantify outcomes from comparable work, and place the most relevant evidence near the top of the resume. When the employer explicitly names tools, platforms, leadership scope, or domain experience, use those source terms accurately and in context.

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We organize source-provided information into this independent job-seeker overview. Compensation is shown only when the source provides it; the official listing remains the authority for current requirements and application instructions.