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Senior Principal Research Engineer, Optimization
RTX
Hartford, USA
Full-time
Senior · 10+ years experience
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- At RTX, the world's largest aerospace and defense company, 185,000 great minds are united by purpose and inspired to make a difference solving the world’s most complex problems. With our three market leading businesses, world-class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Join us and help shape the future of aerospace and defense.
What You Will Do
- Provide technical expertise in the areas of discrete optimization, deep learning for computer vision, large language models (LLMs), vision-language models (VLMs), and state of the art methods for operations planning and scheduling. Of particular interest are demonstrated skills in these areas for industrial problems. Design and develop advanced optimization and machine learning solutions to complex decision-making problems in aerospace and defense applications. Develop and deploy deep learning models to solve challenging computer vision problems. Explore and integrate large language models (LLMs) and vision-language models (VLMs) for multimodal tasks. Lead and support externally and internally sponsored programs, writing external and internal research proposals. Build relationships to support developing business relationships with industry, academia, and government agencies. Disseminate research results through reports, conference proceedings, and peer-reviewed articles, and developing intellectual property.
- Qualifications You Must Have
- Ph.D. in Operations Research, Computer Science, Applied Mathematics, or a related field, with 5+ years of industrial experience.
- Having expertise in one or more of the following areas: A strong background and understanding of mathematical programming; Expertise in designing and training deep neural networks for vision-related tasks; Familiarity with large language models (LLMs) and their integration into vision-language applications.
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