Founding AI Platform Engineer (MLOps / Backend)
Tasks
- Build ML model training infrastructure
- Build backend APIs for AI services
- Build data and configuration pipelines for ML
- Build experimentation and measurement infrastructure
- Build model evaluation pipelines
- Build monitoring for model behavior
- Build retrieval and search infrastructure
- Collaborate with ML and product teams
- Define engineering standards and platform practices
- Deploy ML models
- Establish prompt versioning workflows
- Implement automated testing
- Implement reproducibility for models and datasets
- Improve CI/CD pipelines
- Improve security and performance
- Manage release rollback and environments
- Optimize infrastructure cost efficiency
- Serve ML models in production
- Set up observability for applications and models
- Strengthen reliability and scalability
- Troubleshoot production issues end-to-end
Perks/Benefits
Skills/Tech-stack
APIs | Automated testing | Backend Services | CI/CD | Cloud infrastructure | Cost Optimization | Event Pipelines | Experimentation | Infrastructure as Code | MLOps | Model Monitoring | Model Serving | Monitoring | Observability | Performance optimization | Production reliability | Prompt versioning | Python | Release Management | Reproducibility | Retrieval | Scalability | Search | Security | Vector Databases | “as-code”
Education
N/A
Roles
AI | AI Platform Engineer | Backend | Backend Engineer | Engineer | MLOps Engineer | Platform Engineer
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