About the role
AI summarisedSenior Data Scientist at GE Aerospace in Singapore, leading development of computer vision and multimodal models for defect detection in aerospace manufacturing. Role involves end-to-end model development, co-design of digital inspection solutions with hardware, and collaboration with data engineers and domain experts to deploy scalable AI solutions on the shop floor.
AerospaceFull-timeDigital Technology / IT
Key Responsibilities
- Lead end‑to‑end development of computer vision and multimodal models for defect detection, segmentation, classification and anomaly detection.
- 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.
- Co‑design AI‑ready, repeatable inspection cells and workflows, considering hardware constraints, takt time and shop‑floor 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 / bronze‑silver‑gold layers on Databricks, AWS S3).
- Contribute to scalable model deployment and monitoring in production environments (on‑prem, cloud, and edge devices where applicable).
- Work with inspection specialists, shop operations and repair engineers to understand inspection methods (visual, X‑ray, ultrasonic, eddy current, thermal, etc.) and business requirements.
- Translate shop‑floor 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.
Requirements
- 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, problem‑solving and influencing skills; comfortable in an ambiguous, fast‑evolving environment.
- Quick learner, strategically prioritizes work, committed.
- Strong communicator, decision-maker, collaborative.
- Analytical-minded, challenges existing processes, critical thinker.