You will combine scientific rigor with a pragmatic engineering mindset to bridge research, implementation, and measurable impact. * Design and implement prototypes and proof-of-concepts spanning backend systems, cloud platforms, and AI/ML components. * PhD in Computer Science, Machine Learning/AI, Data Science, Software Engineering, or a closely related field. * Solid engineering skills across ML and software systems, including Python, modern ML tooling, and backend/cloud architectures.
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