AI/ML Engineer
Tasks
- Build model serving platforms for inference
- Build reusable AI ML components and libraries
- Collaborate with data engineers on AI ML data pipelines
- Create AI ML orchestration utilities
- Design build and maintain AI ML lifecycle services
- Design model monitoring and performance tracking
- Develop testing frameworks for AI ML components
- Develop tools for model explainability
- Develop tools for model interpretability
- Develop training validation and deployment infrastructure
- Document AI ML systems and processes
- Implement MLOps continuous integration and deployment
- Implement automated machine learning pipelines
- Implement version control for models and datasets
- Optimize AI ML algorithms for performance and scalability
- Provide technical guidance to data scientists
- Troubleshoot complex AI/ML system issues
Perks/Benefits
- N/A
Skills/Tech-stack
Automated Machine Learning | Continuous Deployment | Continuous integration | Data Pipelines | MLOps | Machine Learning | Model Explainability | Model Interpretability | Model Monitoring | Model Serving | Orchestration | Performance Tracking | Testing Frameworks | Version control
Education
Roles
AI | AI/ML Engineer | Engineer | Learning Engineer | ML Engineer | Machine Learning Engineer
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