Senior Data Scientist
Summary
Build AI-powered computer-vision models for jet-engine inspection, integrating cameras, lasers and NDT hardware into production inspection cells.
- Lead endtoend development of computer vision and multimodal models for defect detection, segmentation, classification and anomaly defection.
- Design experiments, select appropriate algorithms, define success metrics, and drive model iteration.
- Define data and imaging requirements for cameras, lighting, laser/optical sensors and NDT equipment.
- Codesign AIready, repeatable inspection cells and workflows, considering hardware constraints, takt time and shopfloor conditions.
- Support feasibility studies and PoCs integrating AI with robotic and NDT systems.
- Partner with data engineers on ETL pipelines and data architecture (e.g. data lake / bronzesilvergold layers on Databricks, AWS S3).
- Contribute to scalable model deployment and monitoring in production environments (onprem, cloud, and edge devices where applicable).
- Work with inspection specialists, shop operations and repair engineers to understand inspection methods (visual, Xray, ultrasonic, eddy current, thermal, etc.) and business requirements.
- Translate shopfloor workflows, inspection standards and quality criteria into data science problems and product features.
- Collaborate with application developers and UX engineers to integrate models into digital inspection applications, workstations and dashboards.
- The ideal candidate combines strong hands-on experience in computer vision and deep learning with a practical mindset for deploying models in real industrial environments. They are comfortable working at the intersection of AI, imaging and automation, collaborating closely with inspection, robotics and NDT engineers to turn complex shop-floor inspection workflows into robust, repeatable and scalable digital inspection solutions.
- Master's or PhD in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, Applied Mathematics, Statistics, or a related quantitative field.
- Candidates with a Bachelor's degree in a relevant discipline and strong, proven industry experience in computer vision, deep learning or industrial inspection are also encouraged to apply.
- Additional coursework, certifications or research experience in machine learning, deep learning, computer vision, NDT, robotics or industrial automation will be considered a strong plus.
- 5+ years in data science / ML, including 3+ years in computer vision or industrial inspection.
- Strong foundations in ML/DL; experience with CNNs, transformers, segmentation, object detection, and anomaly detection.
- Strong collaboration, problemsolving and influencing skills; comfortable in an ambiguous, fastevolving environment.
- Quick learner, strategically prioritizes work, committed
- Strong communicator, decision-maker, collaborative
- analytical-minded, challenges existing processes, critical thinker