Oura
Senior Manufacturing Data Science & Machine Learning Engineer
$173K–$203K
Hybrid - San Francisco, California +1 · Senior · Full-time · Posted Oct 22, 2026
- Location
- Hybrid - San Francisco, California
San Francisco, CA, United States - Experience
- 5 to 8 years of relevant experience, or an equivalent combination of experience.
- Education
- Bachelor’s or master’s degree in computer science, electrical engineering, mechanical engineering, manufacturing engineering, robotics, data science, or a related field.
About the job
Build and deploy manufacturing data systems, machine-vision and machine-learning solutions, and analytics to improve production quality, yield, process control, and traceability across suppliers.
What you'll do
- Integrate manufacturing data systems and establish data-quality, traceability, and monitoring standards.
- Develop and deploy machine-vision and ML solutions, automated analysis, dashboards, and alerts for production operations.
- Lead manufacturing intelligence workstreams through NPI and mass production, working with suppliers, vendors, and cross-functional teams.
What they ask for
- Bachelor’s or master’s degree in a related field.
- Experience deploying software, analytics, or machine-learning solutions in a factory, lab, warehouse, or other production environment.
- Strong Python skills and experience with data-processing and machine-learning libraries; computer vision and image-processing experience.
- Understanding of MES, manufacturing test systems, equipment interfaces, PLC or industrial-control data, and unit-level traceability.
Nice to have
- Experience integrating factory inspection equipment or related hardware.
- Experience with digital manufacturing, simulation, digital twins, factory capacity modeling, or high-volume consumer-electronics manufacturing.
Pay
$172,550 - $203,000 USD base salary
Tools
Python, pandas, NumPy, scikit-learn, PyTorch, TensorFlow, OpenCV, MES
AI focus
Develop and deploy machine-vision and machine-learning systems for inspection, defect and anomaly detection, process analysis, and production optimization.
Model-written summary · the original posting is authoritative