Senior AI/ML Engineer
Tasks
- Apply secure by design model governance
- Architect machine learning solutions
- Build AI agents for safety analytics
- Build CI/CD for ML
- Collaborate in Agile teams to deliver iterative improvements
- Create monitoring for drift bias and data quality
- Design data ingestion transformation validation pipelines
- Enforce data contracts and data lineage
- Establish MLOps workflows
- Implement experiment tracking and model registry
- Implement machine learning pipelines
- Implement retrieval pipelines for triage and decision flow
- Integrate agents with APIs event streams dashboards and case management
- Lead model selection training validation optimization calibration
- Mentor engineers and data scientists
- Produce model cards data sheets and deployment records
- Set up automated model rollback
- Support code reviews and knowledge sharing
Perks/Benefits
Skills/Tech-stack
API Integration | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure ML | Azure Machine Learning | Azure Synapse | Azure Synapse Analytics | Bias detection | CI/CD | Data Lake Storage | Data Pipelines | Data Preprocessing | Data Quality | Data Visualization | Data sheets | Deep learning | Event Hubs | Event Stream | Event Stream Processing | Experiment tracking | Explainability | Fairness | Feature Engineering | Feature Stores | Language Processing | MLOps | Machine Learning | Model Cards | Model Governance | Model Monitoring | Model Optimization | Model Registry | Model calibration | Natural Language | Natural Language Processing | Privacy | PyTorch | Python | Responsible AI | Retrieval-Augmented Generation | Stream processing | Supervised Learning | Synapse Analytics | TensorFlow | Unsupervised Learning | Vector Databases
Education
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