Data Preprocessing and Feature Engineering
- How effectively does the employee preprocess and prepare data for AI/ML model training?
- Does the employee engineer relevant features to enhance model performance?
- Does the employee handle data quality issues and missing data appropriately?
Infrastructure and Scaling
- How well does the employee design and maintain AI/ML infrastructure for scalability?
- Does the employee implement auto-scaling and load balancing mechanisms?
- Does the employee ensure efficient resource allocation for AI/ML workloads?
AI/ML Frameworks and Libraries
- How does the employee use popular AI/ML frameworks and libraries for model development?
- Does the employee experiment with different algorithms and techniques?
- Does the employee stay updated on AI/ML advancements?
