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Qatar Mobility Innovations Center
As a junior member of the Technology Developemnt & Applied Research department you will:
Assist in prototyping AI solutions br>Work with senior engineers to build proof-of-concept applications across computer-vision, natural-language, generative AI, and predictive-analytics use cases.
Support model evaluation & benchmarking br>Run experiments, gather performance metrics, and help select the mostappropriate algorithms, features, or hyper-parameters for each project.
Contribute to model packaging & deployment br>Write Dockerfiles, maintain docker-compose (or similar) configurations, and learn modern MLOps practices for taking models from notebook to production.
Help build and maintain data pipelines br>Ingest, clean, and transform structured and unstructured data sets that fuel our machine-learning workflows and analytics dashboards.
Write clean, testable Python code br>Develop reusable utilities, unit tests, and Jupyter notebooks under the guidance of senior developers.
Document and present your work br>Create concise reports, dashboards, and short demos for both technical and non-technical stakeholders.
Stay curious and up-to-date br>Follow the latest AI/ML research and industry trends, sharing noteworthy papers, tools, or tutorials with the team.
Must-Have (Day 1)
Bachelor s degree in AI, Data Science, Computer Science, or a closely related field (class of 2024 or 2025).
Solid Python fundamentals: data structures, OOP principles, and working with virtual environments.
Introductory knowledge of machine-learning workflows: model training, evaluation metrics, and the basics of overfitting vs. underfitting.
Eagerness to learn, clear communication style, and a collaborative mindset.
Nice-to-Have (Learn with Us)
Coursework or academic projects involving large-language models, computer vision, signal processing, or similar AI domains.
Familiarity with deep-learning frameworks such as PyTorch and TensorFlow.
A hands-on internship or capstone project that went beyond classroom assignments.
Experience containerizing an application with Docker.
Awareness of MLOps practices (CI/CD, monitoring, model versioning).
If you meet most of the Must-Have items, we still encourage you to apply even if the Nice-to-Have list feels ambitious. We ll help you grow!
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