Senior Manufacturing Data Science & Machine Vision Engineer

Oura; San Francisco (CA); Hybrid; USD 173,000 - 203,000; Full time

Benefits offered by this job

Health, dental, vision insurance

Paid time off: 20 days

13 paid holidays

Wellness time off: 8 days

Parental leave

Employee discounts

Job summary

Ōura seeks a Senior Manufacturing Data Science & Machine Vision Engineer to build an intelligence layer for global manufacturing. In a hands-on role, you will integrate factory images, deploy ML models, MES data, test results, and material genealogy into reliable production capabilities across the supplier network.

You will deploy vision systems, design data-labeling workflows, and develop analytics to improve yield, traceability, and process control while collaborating with cross-functional

Qualifications

• 5–8 years of relevant experience in manufacturing software, industrial data science, machine vision, automation, or equivalent.
• Bachelor’s or master’s degree in computer science, electrical/mechanical engineering, manufacturing engineering, robotics, data science, or related field.
• Experience deploying software, analytics, or machine-learning solutions in a factory, lab, warehouse, or production environment.
• Strong Python programming skills and libraries such as pandas, NumPy, scikit-learn, PyTorch, or TensorFlow.
• Experience with computer vision and image-processing techniques (OpenCV, classification, object detection, segmentation, OCR/OCV, anomaly detection).
• Understanding MES, manufacturing test systems, equipment interfaces, PLC or industrial data, and traceability concepts.
• Willingness to travel regularly to manufacturing sites in Asia and other supplier locations.

Responsibilities

• Build manufacturing data foundations and end-to-end data systems.
• Architect and integrate data systems across the supplier network to capture accurate production data.
• Standardize data models and improve traceability from raw components to final shipment.
• Establish data-quality checks and monitoring frameworks for reliable decisions.
• Develop machine-vision systems for the factory.
• Design and deploy end-to-end vision systems with hardware specs and robust algorithms.
• Establish data-labeling workflows and model validation for actionable insights.
• Automate manufacturing analysis to detect defects and process drift.
• Implement dashboards and alerts linking images with process parameters.
• Collaborate with manufacturers and vendors to define requirements and deployment standards.
• Lead data/vision workstreams through all NPI phases to mass production.
• Create reusable analytics libraries to scale insights across programs.

Skills

Manufacturing data science

Machine vision

Python

Data processing

Education

Bachelor’s or Master’s degree in CS/EE/ME/Robotics/Data Science

Tools

OpenCV

PyTorch

TensorFlow

scikit-learn

Job description

Our mission at the company 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 the company 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.

the company 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 the company’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 software, analytics, or machine‑learning solutions in a factory, lab, warehouse, or other production environment.

• Strong Python programming skills and experience with data‑processing and machine‑learning libraries such as pandas, NumPy, scikit‑learn, PyTorch, or TensorFlow.

• Experience with computer vision and image‑processing techniques, such as OpenCV, image classification, object detection, segmentation, OCR/OCV, anomaly detection, or metrology.

• Understanding of MES, manufacturing test systems, equipment interfaces, PLC or industrial‑control data, and unit‑level traceability concepts.

• Experience with statistical methods, design of experiments, process capability, SPC, measurement‑system analysis, or manufacturing‑quality analysis.

• Demonstrated ability to work directly with contract manufacturers, suppliers, equipment vendors, and cross‑functional engineering teams.

• Willingness and ability to travel regularly to manufacturing sites in Asia and other supplier locations.

Nice to have:

• Experience integrating cameras, lighting, lenses, barcode readers, robots, PLCs, motion systems, or automated inspection equipment.

• Experience with digital manufacturing, discrete‑event simulation, digital twins, or factory capacity modeling.

• Experience with electronics, battery, precision assembly, SMT, molding, coatings, laser processing, or other high‑volume consumer‑electronics manufacturing processes.

• Strong technical writing and stakeholder‑management skills, including the ability to influence without direct authority.

Benefits

At Ōura, we care about you and your well‑being. Everyone here at Ōura 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 Ōura 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

Ōura 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

A recruiter can determine your Region 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).

the company 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 the company are considered without regard to age, ancestry, color, gender (including pregnancy, childbirth, or related medical conditions), ge