106 coding-"https:"-"Prof"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Carnegie Mellon University
Sort by
Refine Your Search
-
App 3. Incorporating new functionalities in the app and improving the App 4. Working closely with collaborators and maintaining upto date updates about projects, including code bases 5. Contributing
-
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
-
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
-
, Hyper-V, Docker) for testing environments. Experience with static code analysis tools and checking compliance with industry standards. Understanding of safety instrumented systems and standards (IEC 61508
-
containerization and virtualization technologies, including VMware, VirtualBox, PodMan, and Singularity. Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and infrastructure-as-code practices
-
with building codes Other duties as assigned Flexibility, excellence, and passion are vital qualities within the department of Facilities Management. Inclusion, collaboration and cultural sensitivity
-
; 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
-
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
-
; 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
-
systems sufficient to maintain credibility with engineering teams (deep coding expertise not required). Experience navigating complex stakeholder ecosystems involving multiple contractors, oversight