Site Overview
Established in 2000, the John F. Welch Technology Center (JFWTC) in Bengaluru is our multidisciplinary research and engineering center. Engineers and scientists at JFWTC have contributed to hundreds of aviation patents, pioneering breakthroughs in engine technologies, advanced materials, and additive manufacturing.
Role Overview:
Understand business problems and identify opportunities to implement Data Science and artificial intelligence solutions.
Design, develop, and implement computer vision, image processing, and multimodal deep learning solutions across engineering, services, and manufacturing use cases, including vision tasks such as classification, detection, segmentation, tracking, OCR, and self-supervised representation learning
Own the end-to-end pipelines for data acquisition, labeling standards, augmentation, dataset versioning, and governance for large scale image/video datasets
Explore, evaluate, and apply state-of-the-art architectures (e.g., CNNs, Vision Transformers, hybrid CNN‑ViT, diffusion-style, multimodal vision–language) tailored to aerospace imaging modalities.
Understand various business processes pertaining to Analytics Development Process
Collect, preprocess, and analyze large datasets to be used for training and testing machine learning models.
Ensure data quality and integrity throughout the data pipeline.
Conduct experiments to develop model and evaluate model performance and iterate on model improvements.
Work with Data Engineering teams to deploy data science models into production environments.
Monitor and maintain deployed models to ensure they perform as expected.
Work closely with data architects, data engineers, and other stakeholders to understand business requirements and translate them into technical solutions.
Provide technical support and guidance on machine/deep learning-related issues.
Optimize machine learning models for performance, scalability, and efficiency.
Implement techniques to improve model accuracy and reduce computational costs.
Stay up to date with the latest advancements in machine learning, deep learning and artificial intelligence.
Explore and implement new machine learning, deep learning and artificial intelligence techniques and tools to enhance the team's capabilities.
Maintain comprehensive documentation of machine learning, deep learning models, algorithms, and processes.
Ensure knowledge transfer and continuity within the team.
The Ideal Candidate
The ideal candidate should have 5+Years experience into development and deployment of machine learning and deep learning solutions focused on image and video analytics, including computer vision, image processing, multimodal models, statistical methods, and semantic analysis to extract structure and actionable insights from large-scale visual datasets.
Required Qualifications
Masters or PhD degree in Statistics, Machine Learning, Computer Science or related STEM fields (Science, Technology, Engineering and Math) with 5+Years analytics development experience
Proficiency in Python (mandatory).
Proficiency in PyTorch/TensorFlow, CNNs, Vision Transformers, hybrid CNN–ViT, diffusion-style, multimodal vision–language & OCRs.
Strong analytical and problem-solving skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, dynamic environment.
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their machine / deep learning & AI services.
Familiarity with Python web frameworks.
Preferred Qualifications:
Influences PBs on their decisions.
Implements a roadmap.
Evaluates, down selects, and has awareness of advanced models for deriving new features in relation to the source of data.
Can fit parameters for complex physics models.
Develops ongoing hypothesis testing for model validity.
Runs change point assessments and predictive models to project time series.
Executes validation reproducibility, and deployment criteria.
Able to use a variety of approaches (sequential sampling/ experimentation and observational studies) to generate cost-effective and representative samples.
Understand advanced methods to trade off interpretability vs predictive complexity.
Can articulate the top pitfalls and misleading graphical representations.
Proficient with local and distributed operating environments.
At GE Aerospace, we have a relentless dedication to the future of safe and more sustainable flight and believe in our talented people to make it happen. Here, you will have the opportunity to work on really cool things with really smart and collaborative people. Together, we will mobilize a new era of growth in aerospace and defense. Where others stop, we accelerate
Additional InformationRelocation Assistance Provided: Yes
