AI Engineer

Mô tả Công việc
A. JOB PURPOSES:
- As an AI Engineer at De Heus Animal Nutrition, you will play a critical role in designing, developing, and implementing advanced AI and machine learning solutions to enhance our data analytics capabilities. You will work closely with various stakeholders, including Data Engineers, Data Visualization Specialists, Data and Digital Business Partners, and business key stakeholders, to ensure that AI solutions align with business needs and objectives. You will report directly to the Data Solution Architect Lead and collaborate closely with the Solution Architect to integrate AI models into our Azure-based data platform.
B. ACCOUNTABILITIES:
1. Develop and Deploy AI Models
- Build, train, and deploy machine learning models and AI algorithms for applications such as predictive analytics, recommendation systems, and automated decision-making processes.
2. Collaborate with Cross-Functional Teams
- Work closely with the Solution Architect, Data Engineers, Data Visualization Specialists, Data and Digital Business Partners, and business stakeholders to gather requirements and design suitable AI solutions.
3. Data Integration and Processing
- Collaborate with Data Engineers to integrate data from various systems into the Azure platform, using tools like Azure Data Factory and Azure Databricks.
4. Optimize Performance and Monitor Models
- Optimize AI models to improve performance, scalability, and accuracy; monitor and maintain models in production environments.
5. Research and Innovation
- Keep up with the latest advancements in AI, machine learning, and cloud technologies; evaluate new tools and methods that could enhance data analytics capabilities.
6. Documentation and Knowledge Sharing
- Create and maintain detailed documentation for AI models, algorithms, and processes; organize training sessions and knowledge-sharing activities with relevant teams.
C. RESULTS:
- High-accuracy AI models successfully deployed into production environments, meeting or exceeding performance and reliability standards.
- AI solutions developed align with business requirements and seamlessly integrate with existing data processes.
- Data successfully prepared and integrated to support AI model training and deployment, ensuring data quality and availability.
- AI models perform efficiently and stably, with quick response times and optimized operational costs.
- Propose and implement new technologies and methodologies that enhance the performance and value of AI solutions within the company.
- Comprehensive and easy-to-understand documentation supports collaboration and maintenance; enhanced understanding and adoption of AI across the organization.