Oura

1 month ago

Senior AI Engineer – Health Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Senior AI Engineer focusing on building end-to-end AI-powered health guidance at a wearable health company. Responsible for designing LLM-backed workflows, evaluation pipelines, personalization, and multi-LLM platform integration to deliver scalable, safe, user-centered health insights.

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Design and build LLM-backed product capabilities: Ship user-facing features that use LLMs and other AI models to deliver personalized insights, guidance, and proactive notifications. Implement safe tool-calling, retrieval, and orchestration so that AI components behave deterministically where they must and adaptively where they can.
•Own evaluation, quality, and safety for AI workflows: Lead the design and implementation of evaluation frameworks and tooling to measure quality, safety, latency, and cost before and after release. Define the metrics and slices that matter for user-facing guidance, and integrate evals into the production pipeline.
•Integrate LLMs with personalization and understanding layers: Ground AI behavior in structured user context rather than one-off prompts. Connect AI components to navigation flows and action systems so guidance turns into coherent, multi-step programs and one-tap actions, not isolated tips.
•Contribute to a multi-LLM and reasoning platform: Prototype and productionize workflows across multiple model providers and configurations, including routing logic and shadow-mode experimentation. Collaborate with infrastructure and science teams on reasoning, planning, and multimodal use cases.
•Build robust, observable, and cost-aware systems: Design and implement services and workflows that meet reliability and performance expectations. Take ownership of operational health: debugging production issues, reducing technical debt, and iterating on architecture as the AI surface area and traffic grow.

Pay and Benefits

Perks:Health InsuranceDentalVisionEquityPaid LeaveParental Leave

Key Requirements

•2+ years of hands-on experience in AI engineering, with a multi-year background in backend engineering, applied ML, or related roles building production systems.
•Strong proficiency in at least one modern backend or ML language (e.g., Python) and comfort working with cloud-native services to ship and maintain production features.
•Demonstrated ability to own systems end-to-end: from problem framing and data pipelines through modeling and prompting, all the way to deployment, monitoring, and iteration.
•A track record of working in product-facing teams, shipping to real users rather than only research prototypes, and caring about impact and iteration speed.
•Comfort operating in a fast-changing AI/LLM domain with ambiguity, balancing rigor with pragmatism and keeping member value and safety at the center.

Experience:2+ yearsAIBackendMLProduction systems

Skills:PythonLLMsCloud-native servicesData pipelinesProduction systems

Languages:English

Tech Stack:PythonLLMsCloudData pipelines

Company Brief

Oura

Designs and sells the Oura Ring, a wearable device that tracks sleep, activity, and physiological signals to provide personalized health, recovery, and readiness insights via a companion app and analytics platform.

Industry: Wearables

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series C

Headquarters: Oulu, Finland

Founded: 2013

Website LinkedIn

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Oura

1 month ago

Senior AI Engineer – Health Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Design and build LLM-backed product capabilities: Ship user-facing features that use LLMs and other AI models to deliver personalized insights, guidance, and proactive notifications. Implement safe tool-calling, retrieval, and orchestration so that AI components behave deterministically where they must and adaptively where they can.
•Own evaluation, quality, and safety for AI workflows: Lead the design and implementation of evaluation frameworks and tooling to measure quality, safety, latency, and cost before and after release. Define the metrics and slices that matter for user-facing guidance, and integrate evals into the production pipeline.
•Integrate LLMs with personalization and understanding layers: Ground AI behavior in structured user context rather than one-off prompts. Connect AI components to navigation flows and action systems so guidance turns into coherent, multi-step programs and one-tap actions, not isolated tips.
•Contribute to a multi-LLM and reasoning platform: Prototype and productionize workflows across multiple model providers and configurations, including routing logic and shadow-mode experimentation. Collaborate with infrastructure and science teams on reasoning, planning, and multimodal use cases.
•Build robust, observable, and cost-aware systems: Design and implement services and workflows that meet reliability and performance expectations. Take ownership of operational health: debugging production issues, reducing technical debt, and iterating on architecture as the AI surface area and traffic grow.

Pay and Benefits

Perks:Health InsuranceDentalVisionEquityPaid LeaveParental Leave

Key Requirements

•2+ years of hands-on experience in AI engineering, with a multi-year background in backend engineering, applied ML, or related roles building production systems.
•Strong proficiency in at least one modern backend or ML language (e.g., Python) and comfort working with cloud-native services to ship and maintain production features.
•Demonstrated ability to own systems end-to-end: from problem framing and data pipelines through modeling and prompting, all the way to deployment, monitoring, and iteration.
•A track record of working in product-facing teams, shipping to real users rather than only research prototypes, and caring about impact and iteration speed.
•Comfort operating in a fast-changing AI/LLM domain with ambiguity, balancing rigor with pragmatism and keeping member value and safety at the center.

Experience:2+ yearsAIBackendMLProduction systems

Skills:PythonLLMsCloud-native servicesData pipelinesProduction systems

Languages:English

Tech Stack:PythonLLMsCloudData pipelines

Company Brief

Oura

Industry: Wearables

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Funding: Series C

Headquarters: Oulu, Finland

Founded: 2013

Website LinkedIn