Senior ML Backend Engineer
Tasks
- Build machine learning infrastructure for model development and training
- Contribute to architecture decisions for scalability reliability performance and cost
- Design ML pipelines for evaluation deployment and monitoring
- Develop automation testing observability and monitoring for ML systems
- Enable reproducibility data lineage and model governance in ML environments
- Ensure security governance responsible AI and model risk management compliance
- Integrate new data sources technologies and tools to improve model performance
- Manage production operations for scalable machine learning workloads
- Transition models from prototypes to production systems
Perks/Benefits
- Collaborative environment
- Inclusive workplace
- Professional growth opportunities
- Responsible AI and governance exposure
Skills/Tech-stack
Automated Workflows | CI/CD | Containerization | Data Lineage | Deep learning | Distributed Computing | Docker | Experiment tracking | Kubernetes | MLOps | Machine Learning | Model Governance | Model Monitoring | Model Risk Management | Model risk | Observability | Python | Reproducibility | Risk Management
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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