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Artificial intelligence architect

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Publicada el 23 abril
Descripción

Role : Artificial Intelligence Architect

Experience Level : Senior (5+ years of experience in AI and systems architecture)

Job Description :

We are looking for an Artificial Intelligence (AI) Architect with experience in both traditional AI and generative AI to design and lead the implementation of scalable, robust, and efficient solutions. He will be responsible for defining the architecture of solutions based on machine learning, deep learning, and generative AI, ensuring their alignment with business needs and industry best practices.

Responsibilities :

* Design architectures for AI solutions that integrate traditional (Machine Learning, Deep Learning) and generative (LLMs, Diffusion Models, GANs) models.
* Define AI implementation strategies in business environments, ensuring scalability, efficiency, and regulatory compliance.
* Select and evaluate technologies, frameworks, and tools to optimize the development and deployment of AI models.
* Integrate AI solutions with cloud architectures using hyperscale services (AWS, GCP, Azure).
* Monitor the full lifecycle of AI models, from experimentation to production with MLOps, AIOps, or GenAIOps practices.
* Ensure data governance, including quality, security, and regulatory compliance (GDPR, HIPAA, etc.).
* Lead multidisciplinary teams in the development of AI-based solutions.
* Continuously evaluate new AI technologies and their applicability in the business.
* Optimize cloud AI infrastructure costs, ensuring a balance between performance and budget.
* Establish best practices in the development, implementation, and monitoring of AI models.

Requirements :

* Degree in Computer Science, Systems Engineering, Mathematics, or a related field.
* More than 5 years of experience in AI solution architecture, including generative AI.
* Advanced knowledge of AI frameworks such as TensorFlow, PyTorch, Scikit-learn, Hugging Face, and LangChain.
* Experience in generative AI, including LLMs (GPT, LLaMA, Claude) and diffusion models (Stable Diffusion, DALL-E).
* Proficiency in data processing with tools such as Pandas, Spark, and SQL / NoSQL databases.
* Knowledge in vector databases and Generation Augmented Retrieval (RAG) systems.
* Experience in developing AI APIs for internal and external consumption.
* Familiarity with production model optimization techniques (quantization, pruning, distillation).
* Technical leadership skills and communication with stakeholders from different areas.
* Experience in hybrid architectures (Edge AI, on-premise + cloud).
* Certifications in AWS, Azure, or GCP in Machine Learning / AI.
* AI publications or contributions to the open-source community.

Proceeds :

* Opportunity to work on innovative AI projects across multiple sectors.
* Continuous training plan in emerging technologies.
* Remote or hybrid work with flexible schedules.
* Dynamic environment with high-level technical teams.
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