Founding AI Platform Engineer (MLOps / Backend)
Tasks
- Assess platform scaling risks proactively
- Build CI/CD pipelines
- Build ML platform infrastructure
- Build experimentation infrastructure
- Create engineering standards and tooling
- Develop backend APIs and pipelines
- Enable reliable model evaluation
- Ensure reproducibility for models prompts datasets configurations
- Establish observability
- Implement model lifecycle management
- Implement rollback strategies
- Improve automated testing and release processes
- Improve platform reliability scalability security performance
- Maintain ML training evaluation deployment serving
- Manage environments
- Monitor application health model behavior latency costs
- Optimize infrastructure cost efficiency
- Troubleshoot production issues end-to-end
Perks/Benefits
Skills/Tech-stack
Automated testing | Backend APIs | CI/CD | Cloud infrastructure | Cost Optimization | Experimentation | Feature Engineering | GenAI | Latency optimization | MLOps | Machine Learning | Model Deployment | Model Serving | Model Training | Monitoring | Observability | Performance Engineering | Prompt versioning | Python | Reliability Engineering | Reproducibility | Retrieval-Augmented Generation | Scalability | Security | Vector Search
Education
N/A
Roles
AI | AI Platform Engineer | Backend | Backend Engineer | Engineer | MLOps Engineer | Platform Engineer
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