AI/ML Engineer
DKCPH55 - Copenhagen - Esplanaden 50, Denmark
DKK 516K-580K (estimate) Mid-level Full Time
Tasks
- Apply classification and anomaly detection models
- Build AI ML components for data anomaly detection
- Build data profiling and scoring mechanisms
- Deploy and support AI and data quality solutions
- Detect schema drift and data degradation
- Develop data quality validation rules
- Implement responsible AI monitoring and explainability
- Integrate solutions into orchestration and MLOps platforms
- Maintain lifecycle logging for models
- Operationalize data quality ownership
- Perform troubleshooting and root cause analysis
- Support DataOps quality standards
- Use NLP for metadata enrichment
- Write engineering documentation and tests
Perks/Benefits
- N/A
Skills/Tech-stack
Agile | Anomaly Detection | CI/CD | Classification | Cloud Computing | Clustering | Data Observability | Data Pipelines | Data Quality | DataOps | Explainability | MLOps | Machine Learning | Metadata Management | Model Monitoring | NLP | Predictive Analytics | Profiling | Python | Schema drift | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI/ML Engineer | Data Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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