Our client is setting up a brand new AI/ML function and within this capability, we are looking for a Azure AI MLOps Engineer professional. The role is based within the IT department on the AI function.
- Build, develop and deploy AI powered applications using Python and related frameworks
- Utilise Python and other relevant programming languages to build intelligent applications on the Azure platform.
- Design and develop Azure AI Services proficiently; Develop solutions using Azure AI Prompt Flow;
- Setup and develop data ingestion pipelines and components; design and develop efficient ingestion methodologies
- Developing search related components using Azure AI Search (Vector Store)
- Developing and deploying AI/ML models on Azure technologies for business teams
- Work closely with MLOps engineers to Integrate MLOps practices into the existing development lifecycle
- Collaborate with AI Engineers, MLOps Engineers, Data Scientists and Business stakeholders to understand deployment, networking and security requirements in helping design effective AI solutions for the projects
- Develop and test code, ensuring high quality, maintainability, and adherence to best practices.
- Create and maintain secure and performant AI platform
- Provide technical expertise in designing, developing and implementing the AI powered applications
- Develop unit tests, automated regression packs and help setup model evaluation test packs
- Build and maintain scalable, high-performance AI apps on Azure platform.
- Provide technical expertise and support to troubleshoot and resolve AI-related issues and performance bottlenecks.
- Stay current with industry trends and best practices in AI technology and recommend innovative solutions to enhance business operations.
- Conduct thorough testing and validation of AI models to ensure accuracy and reliability.
- Document and communicate AI solutions and recommendations to technical and non-technical stakeholders clearly and effectively.
- Develop and implement automated testing frameworks for machine learning models to ensure their ongoing accuracy and reliability.
- Document AI development processes and procedures for efficient knowledge transfer and maintainability.
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