Founding AI Platform Engineer (MLOps / Backend)
Tasks
- Automate testing for releases
- Build CI/CD pipelines
- Build ML model deployment pipelines
- Build ML model training infrastructure
- Build experimentation measurement infrastructure
- Collaborate with ML and product teams
- Convert recurring incidents into engineering improvements
- Develop backend services/APIs
- Develop data pipelines for ML workflows
- Establish engineering standards
- Implement dataset versioning
- Implement model lifecycle management
- Implement model serving systems
- Implement observability for application health
- Implement observability for latency costs
- Implement observability for model behavior
- Implement prompt versioning
- Implement reproducibility for models prompts datasets
- Implement rollback strategies
- Improve platform cost-efficiency
- Improve platform performance
- Improve platform reliability
- Improve platform scalability
- Improve platform security
- Manage environments and release processes
- Troubleshoot production issues end-to-end
Perks/Benefits
Skills/Tech-stack
Analytics instrumentation | Automated testing | Backend APIs | CI/CD | Cloud infrastructure | Cost Optimization | Event Pipelines | Experimentation | Feature Engineering | GenAI | Latency optimization | MLOps | Machine Learning | Model Serving | Monitoring | Observability | Performance optimization | Prompt engineering | Python | Reliability Engineering | Retrieval-Augmented Generation | Scalability | Security | Vector Databases
Education
N/A
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