Expert AI

2 semanas atrás

Lisboa, Portugal QiBit Tempo inteiro

We are looking for an Expert AI & Data Science Engineer - GenAI to join the IT team of our client – a company specialized in the Telecom sector. What will be your main tasks and responsibilities? Develop and operationalize machine learning and generative AI models for high-impact business use cases; Design and implement data science models, including feature engineering and rapid prototyping; Build and automate AI pipelines, integrating them into business processes and tools; Manage the full AI lifecycle, including MLOps, monitoring, retraining, and governance alignment; Design and deploy GenAI applications for use cases such as content summarization, intelligent document processing, and chatbot assistants; Ensure performance optimization and cost-efficiency of AI models in cloud environments; Collaborate with data engineers and architects to align AI components with enterprise data architecture; Work closely with BI and automation teams to operationalize AI insights across platforms; Contribute to the standardization of reusable GenAI components, prompts, and evaluation techniques; Ensure alignment with responsible AI guidelines, data privacy requirements, and IT security standards; Translate complex AI models into actionable business insights through compelling storytelling; Monitor new trends in GenAI and identify opportunities for innovation and impact. What will be required from you? Degree in Data Science, Computer Science, Statistics, or a similar area; At least three years of experience in building and deploying machine learning models, preferably with cloud-based AI services, preferably on Google Cloud Platform (e.g. Vertex AI, AutoML, BigQuery ML); Strong proficiency in Python, with experience in ML and GenAI libraries (e.g. scikit-learn, TensorFlow, Hugging Face, OpenAI SDK); Experience developing and deploying LLM-based applications (chatbots, summarizers, semantic search); Knowledge of MLOps and GenAIOps workflows, model retraining, and monitoring; Understanding of GenAI architectural patterns such as RAG, agentic workflows, and embedding stores; Strong command of SQL and working with structured and semi-structured data; Familiarity with APIs and tools for integrating GenAI capabilities into enterprise applications; Extensive professional experience in distributed, multinational and complex organizations; Strong stakeholder communication skills, including the ability to explain AI/GenAI capabilities and limitations; Curiosity, adaptability, and a drive to stay ahead of AI innovation trends; Fluency in English both written and spoken. Sounds like you? Send us your CV and let's talk

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