Senior Manufacturing Data Science & Machine Vision Engineer

Job description

Our mission at Oura 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. Oura is seeking a Senior Manufacturing Data Science & Machine Vision Engineer to build an intelligence layer for global manufacturing. In this hands-on, supplier-facing role, you will integrate factory images, deploy ML models, equipment signals, MES data, test results, and material genealogy into reliable production capabilities.You will deploy machine-vision and machine-learning solutions to enhance inspection, yield, process control, root-cause analysis, and traceability across contract manufacturers and suppliers. This role suits an engineer capable of working across factory floors, Python notebooks, and production data pipelines to deliver practical, robust analytics. What You Will Do: • Build manufacturing data foundations • Architect and integrate end-to-end manufacturing data systems (MES, testers, cloud) across the supplier network to capture accurate production data. • Standardize data models and improve traceability to ensure data integrity from raw components through to final product shipment. • Establish robust data-quality checks, validation rules, and monitoring frameworks to drive reliable operational decision-making. • Develop machine-vision systems for the factory • Identify and implement high-value machine vision and image-based inspection opportunities across factory operations. • Design and deploy end-to-end vision systems, covering hardware specifications (optics, cameras, lighting) and the development of robust classical and deep-learning algorithms. • Establish data-labeling workflows and model validation frameworks to translate vision insights into actionable manufacturing decisions that optimize yield and quality. • Automate manufacturing analysis • Build and deploy automated analysis engines and ML/Vision models to detect process drift, defects, and anomalies directly in the production environment. • Implement automated dashboards and alerts, correlating images with process parameters and test data to accelerate root-cause analysis and prevent yield loss. • Develop reusable analytics libraries and tools to scale data-driven insights across Oura’s manufacturing programs and partner network. • Explore digital-twin and simulation approaches to model manufacturing scenarios, line capacity, and process flows to optimize production before hardware availability. • Drive deployment and strategy • Lead the technical execution of data, machine-vision, and analytics workstreams through all NPI phases, from EVT and DVT to mass production and sustaining. • Collaborate with cross-functional teams, contract manufacturers, and equipment vendors to define technical requirements, acceptance criteria, and robust deployment/maintenance standards for production systems. • Identify and prioritize high-impact opportunities in industrial AI, vision, and connected manufacturing to address production pain points and optimize quality, yield, and cycle time. • Define and communicate the long-term manufacturing intelligence roadmap, establishing reusable data/vision standards and effectively influencing leadership and stakeholders on technical investments. This is a hybrid role out of our San Francisco office. What you'll bring • 5 to 8 years of relevant experience in manufacturing software, industrial data science, machine vision, automation, test engineering, supplier development, or an equivalent combination of experience. • Bachelor’s or master’s degree in computer science, electrical engineering, mechanical engineering, manufacturing engineering, robotics, data science, or a related field. • Experience deploying softwa