Head of Machine Learning Operations
Tasks
- Advise senior leadership
- Automate ML deployment
- Build release management tools
- Collaborate with stakeholders
- Conduct ML engineering research
- Create Data Science DevOps roadmap
- Develop MLOps software tools
- Drive MLOps strategy
- Establish model governance lifecycle
- Evaluate emerging technologies
- Implement CI/CD pipelines
- Improve system architecture
- Lead proof-of-concepts
- Maintain MLOps pipeline tools
- Manage ML operations platforms
- Manage source code management
- Mentor and coach team members
- Monitor refresh ML models
- Perform exploratory data analysis
- Provide escalation for technical issues
- Serve ML models to production
- Write production Python code
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Agile | CI/CD | Design Patterns | Docker | Google Cloud | Infrastructure as Code | Integration Testing | Jenkins | Kubernetes | Learning operations | Logging | Machine Learning | Machine Learning Operations | Model Governance | Monitoring | Object-Oriented | Object-oriented programming | Python | Release Management | Unit Testing | Version control | “as-code”
Education
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