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AI Engineer

Porto

Job description

We are seeking a Senior AI Engineer specializing in Azure OpenAI and Predictive Analytics to join our dynamic team. In this role, you will lead the design, development, and deployment of AI-driven solutions, leveraging the Azure AI/ML ecosystem to address complex business challenges. You will collaborate closely with Product Owners to rapidly prototype, test, and refine models, ensuring alignment with evolving business needs.

Key Responsibilities:

• Design and implement AI models using Azure OpenAI, Azure Machine Learning, and Cognitive Services.

• Develop predictive analytics solutions, including time series forecasting, regression models, anomaly detection, and clustering.

• Integrate AI models with various data sources and enable insights through visualization tools such as PowerBI

• Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.

• Engage in rapid prototyping, embracing a “fail fast and adapt” mindset to iterate and improve models based on feedback.

• Stay abreast of the latest developments in AI and machine learning to ensure our solutions remain cutting-edge.

Requirements

You Rock at:

• Proven experience as an AI Engineer or similar role, with a strong focus on Azure AI and Machine Learning services.

• Proficiency in Python (pandas), SQL, NLP

• Experience integrating insights in consumers such as web applications or Power BI

• Deep understanding of machine learning algorithms and statistical modeling techniques.

• Experience with time series forecasting, regression analysis, anomaly detection, and clustering methods.

• Ability to work in an agile environment, rapidly prototyping and iterating on solutions.

• Strong problem-solving skills and the ability to work independently as well as part of a team.

• Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.

Nice to Have:

• Experience with other cloud platforms and AI services.

• Familiarity with DevOps practices and tools.

• Knowledge of data engineering and data pipeline construction.

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