98 coding-"https:"-"FEMTO-ST"-"CSIC" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at Carnegie Mellon University
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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
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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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with professional engineers and researchers Willingness to learn new technologies with cross-functional teams Potential to analyze code and system architectures to identify vulnerabilities Skills in
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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
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systems sufficient to maintain credibility with engineering teams (deep coding expertise not required). Experience navigating complex stakeholder ecosystems involving multiple contractors, oversight
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software-intensive systems sufficient to maintain credibility with engineering teams (deep coding expertise not required). Experience navigating complex stakeholder ecosystems involving multiple contractors
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their tradecraft to exploit those vulnerabilities. Reverse engineer malicious code in support of high-impact customers, design and develop new analysis methods and tools, work to identify and address emerging and
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requirements. Supply & Safety Management: Requisition necessary parts and materials while ensuring all work complies with safety regulations, building codes, and university policies. Other duties as assigned
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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
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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