Aprio Colombia - AI Engineer
Tasks
- Architect data pipelines
- Build and test AI models
- Build proof-of-concepts
- Containerize applications
- Create AI model documentation
- Deploy AI models on Azure
- Design AI/ML solutions
- Develop APIs and integrations
- Develop and deploy machine learning models
- Ensure data privacy and ethical AI compliance
- Identify AI use cases
- Implement CI/CD pipelines
- Implement infrastructure-as-code
- Optimize model performance
- Provide technical guidance
- Provide training and support
- Set up MLOps monitoring
- Stay current with AI advancements
- Translate business requirements into technical specifications
Perks/Benefits
- N/A
Skills/Tech-stack
Azure Cognitive | Azure Cognitive Services | Azure Data | Azure Data Factory | Azure Kubernetes | Azure Kubernetes Service | Azure Machine Learning | Azure Synapse | Azure Synapse Analytics | C# | CI/CD | Cognitive Services | Data Factory | Docker | Dynamics 365 | Fine Tuning | Infrastructure as Code | JavaScript | Kubernetes | Kubernetes Service | Langchain | Language Models | Large Language Models | MLOps | Machine Learning | Microsoft Dynamics | Microsoft Dynamics 365 | Microsoft Power | Microsoft Power Apps | Microsoft Power Automate | Microsoft Power BI | NoSQL | Power Apps | Power Automate | Power BI | Prompt engineering | PyTorch | Python | R | Retrieval-Augmented Generation | SQL | Scikit-learn | Semantic Kernel | SharePoint | Synapse Analytics | TensorFlow | Vector Databases | “as-code”
Education
N/A
Roles
AI | AI Engineer | Engineer
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