AI Architect

<h3>📋 Description</h3> • 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. <h3>🎯 Requirements</h3> • 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. • Cloud AI Services Expertise: o AWS: SageMaker, Bedrock, Comprehend, Rekognition. • Azure: Azure Machine Learning, OpenAI Service, Cognitive Services. • Google Cloud: Vertex AI, AutoML, Generative AI Studio. • Knowledge in MLOps (CI/CD for models, MLflow, Kubeflow, Docker, Kubernetes). • 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. <h3>🏖️ Benefits</h3> • 23 días de vacaciones • Buen clima laboral • Acceso ilimitado a formación tecnológica puntera en modalidad barra libre. • Club de beneficios para empleados con descuentos directos y miles de ofertas en marcas, hoteles, agencias de viaje, cines, ropa…