Senior ML Backend Engineer
Tasks
- Apply responsible AI practices
- Build ML infrastructure
- Containerize ML workloads
- Contribute to ML architecture decisions
- Deploy and monitor ML models
- Design scalable ML platforms
- Develop MLOps automation
- Ensure reproducibility
- Evaluate model performance
- Implement experiment tracking
- Implement model monitoring
- Improve system security and risk management
- Integrate new data sources
- Maintain ML pipelines
- Manage data lineage
- Operate distributed training
- Support model governance
Perks/Benefits
- Collaborative environment
- Exposure to advanced ML challenges
- Inclusive workplace
- Professional growth opportunities
Skills/Tech-stack
Automated Workflows | CI/CD | Cloud Native | Containerization | Data Governance | Data Lineage | Deep learning | Distributed Computing | Docker | Experiment tracking | Kubernetes | LLM | Language Models | Large Language Models | MLOps | Machine Learning | Model Governance | Model Monitoring | Observability | Python | Reproducibility | Version control
Education
Bachelor of Engineering | Bachelor of Science | Master of Science | PhD
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