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AI Solutions Architect

hace 2 semanas


Madrid, Madrid, España Vodafone A tiempo completo

Would you like to be part of our new adventure? Vodafone Group launched its new technological HUB in 2021, an international center of excellence dedicated to research and development of technical solutions, such as Secure Networks, 5G and 6G development, Open RAN, IoT, MPN & MEC and UCC for Vodafone Business, platforms and enterprise solutions.

This vacancy is part of VOIS Spain, a legal entity part of Vodafone Group.

Come and join us to create the future together

At Vodafone, our strategy revolves around three core pillars: Customer, Simplicity, and Growth. As we focus on enhancing our internal capabilities in AI, Machine Learning, and Generative AI, the role of an AI Solution Architect becomes pivotal. This role will support our technology department in driving innovation, improving customer experiences, and simplifying our operations through advanced AI solutions.

The AI Solution Architect will be responsible for designing and implementing the architecture of AI solutions that align with Vodafone's strategic goals with a clear focus on scalability, robustness, security, modular and reusable components. This role involves collaborating with cross-functional teams to reach the aforementioned objectives. The AI Architect will play a crucial role in driving innovation and enhancing Vodafone's data-driven decision-making processes.

You will have the following responsibilities:

  1. Design and implement AI architectures that align with Vodafone's strategic goals.
  2. Collaborate with data scientists, software engineers, and other stakeholders to develop and integrate AI solutions.
  3. Ensure the scalability, efficiency, and security of AI solutions.
  4. Stay updated with the latest advancements in AI and related technologies and apply them to improve existing solutions.
  5. Provide technical leadership and guidance to the AI development team.

What you bring:

  1. Strong experience with AI and machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch).
  2. Proficiency in programming languages such as Python, Java, or C++.
  3. In-depth knowledge of cloud platforms, with Google Cloud being the most important, followed by AWS and Azure.
  4. Experience with data processing and storage technologies (e.g., Hadoop, Spark, SQL).
  5. Understanding of DevOps practices and tools for continuous integration and deployment.
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