Head of AI Engineering
Tasks
- Architect ML platform
- Build end-to-end ML solutions
- Contribute to system architecture
- Define AI ML lifecycle best practices
- Engage with clients on technical solutions
- Establish career paths and performance standards
- Establish data governance and pipelines
- Evaluate experiments and select approaches
- Hire, coach, and mentor engineers
- Integrate generative AI into workflows
- Lead AI ML and data engineering teams
- Monitor model performance
- Oversee model training and deployment
- Own engineering deliverables
- Present technical trade-offs
- Run Agile/Scrum processes
- Translate business objectives into technical roadmaps
Perks/Benefits
Skills/Tech-stack
AWS | CI/CD | Cloud platform | Data Engineering | Data Governance | Data Pipelines | Generative AI | Google Cloud | Google Cloud Platform | Lifecycle Management | ML Lifecycle | ML Lifecycle Management | MLOps | Machine Learning | Microsoft Azure | Model Optimization | Model Training | Scalable System Design | System Architecture | System design
Education
N/A
Roles
AI Engineering | Engineering | Engineering Manager | Head | Head of AI | Head of AI Engineering | Manager
Regions
Countries
States
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