Founding AI Platform Engineer (MLOps / Backend)
Tasks
- Build and maintain ML model deployment infrastructure
- Build and maintain ML model serving infrastructure
- Build and maintain ML model training infrastructure
- Build and maintain model monitoring observability
- Build reproducibility for models and datasets
- Convert recurring issues into engineering improvements
- Develop backend services and APIs for AI workflows
- Develop data pipelines for model lifecycle management
- Establish application and model observability
- Implement automated testing and release processes
- Implement lifecycle management for prompts and prompts datasets
- Implement rollback strategies
- Improve CI/CD pipelines
- Improve platform reliability and scalability
- Improve platform security and performance
- Manage deployment environments
- Optimize infrastructure cost efficiency
- Support experimentation and measurement infrastructure
- Troubleshoot production issues end-to-end
Perks/Benefits
Skills/Tech-stack
API Development | Automated testing | Backend Development | CI/CD | Cloud infrastructure | Experimentation | GenAI | Infrastructure as Code | Language Models | Large Language Models | Latency optimization | Logging | MLOps | Machine Learning | Metrics | Model Deployment | Model Serving | Monitoring | Observability | Performance Tuning | Pipeline Orchestration | Python | REST APIs | Reliability Engineering | Scalability | Security | Tracing | “as-code”
Education
N/A
Roles
AI | AI Platform Engineer | Engineer | MLOps Engineer | Platform | Platform Engineer
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