Technical Lead

• Develop and implement algorithms to process aerospace visual data (e.g., images, video, sensor data) for tasks such as defect detection, damage assessment, visual search, and anomaly detection.
• Apply deep learning and modern computer vision techniques (e.g., CNNs, vision transformers, detection and segmentation networks) to real-world aerospace problems.
• Design experiments, define metrics, and conduct rigorous evaluations to validate model and system performance.
• Integrate AI/ML models with physics-based understanding of systems, leveraging modeling, optimization, estimation, or detection technologies to improve performance and robustness.
• Validate solutions through simulation and on-target products, maturing technologies for transfer to GE Aerospace businesses.
• Document technologies and results through patent applications, technical reports, and publications.
• Collaborate in a multidisciplinary environment and communicate results and recommendations to technical peers and business stakeholders.

You will address challenges unique to the aerospace domain, including varying operating conditions, complex 3D geometries, multimodal data (e.g., image + text + sensor), data quality constraints, and integration of AI solutions into safety-critical and regulated workflows.

Required Qualifications

• Master's degree in Computer Science, Electrical, Electronics, Mechanical, Aerospace, or related Engineering field with specialization in Computer Vision, Machine Learning, AI, or a related area, and 3+ years of relevant experience;
  OR PhD in a related field.
• Demonstrated experience in deep learning for vision, including one or more of:
  • Image classification, object detection, segmentation
  • Anomaly/defect detection, 3D vision, or multi-view geometry
• Proficiency in Python and at least one deep learning framework (e.g., PyTorch, TensorFlow).
• Experience implementing data pipelines, training/evaluation code, and deploying models in experimental or pilot settings.
• Knowledge and application of data analytics, optimization, estimation, or detection algorithms.
• Self-starter with the ability to work in ambiguous environments and strong communication and teamwork skills.