138 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "St" uni jobs at Carnegie Mellon University
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Institute’s mission as a federally funded research and development center (FFRDC) sponsored by the U.S. Department of War. This position combines hands-on financial analysis with team leadership
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computing, you will identify, shape, apply, conduct, and lead research in support of critical U.S. government needs. The ideal candidate will have a strong background with hands-on experience in one or more
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unacceptable risk. Position Summary: As a Senior Autonomous Systems Research Scientist you will identify, lead, and conduct research in support of critical U.S. government needs. The ideal candidate will have a
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that delivers timely and high-quality results. We’re looking for a creative engineering student to design and develop software prototypes, find weaknesses in source code and research methods for software
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Temporary Data Engineer (with Apache Airflow 2.0 and 3.0 experience) - Temporary Employment Services
. Pipeline Development: Modify and develop complex data applications and system programs based on detailed technical specifications. Quality Assurance: Code, test, and debug programs to ensure data integrity
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AI systems and how attackers adapt their tradecraft to exploit those vulnerabilities. Reverse engineer malicious code in support of high-impact customers, design and develop new analysis methods and
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, and code review Diagnosing and resolving issues across the full stack to ensure a smooth, reliable user experience Supporting a team culture that values learning, knowledge‑sharing, and supportive
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Temporary Data Engineer (with Apache Airflow 2.0 and 3.0 experience) - Temporary Employment Services
. Pipeline Development: Modify and develop complex data applications and system programs based on detailed technical specifications. Quality Assurance: Code, test, and debug programs to ensure data integrity
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issues and develop reliable, repeatable solutions Writing clean, maintainable code and contributing to long‑term architecture decisions Participating in testing, validation, and documentation to ensure
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; comfortable developing production-grade code and APIs. Solid understanding of ML theory, statistical learning, and common algorithms. Hands-on experience with TensorFlow, PyTorch, Torch, Caffe, or similar deep