Founding AI Platform Engineer (MLOps / Backend)
Tasks
- Build and maintain ML model training evaluation deployment serving monitoring infrastructure
- Build reproducibility and lifecycle management for models prompts datasets configurations and releases
- Collaborate with ML product and engineering teams to deliver platform solutions
- Define engineering standards tooling and reliability practices
- Develop and operate production backend services APIs and pipelines for ML and GenAI
- Enable experimentation and measurement infrastructure for ML and product teams
- Establish observability for application health model behavior agent quality latency costs and failures
- Improve CI/CD pipelines automated testing release processes rollback strategies and environment management
- Strengthen platform reliability scalability security performance and cost efficiency
- Troubleshoot production issues end to end and drive engineering improvements
Perks/Benefits
Skills/Tech-stack
Automated testing | Backend APIs | CI/CD | Cloud infrastructure | Cost Optimization | Data analytics | Event Pipelines | Experimentation | Feature delivery | GenAI | Infrastructure as Code | Latency optimization | MLOps | Machine Learning | Model Deployment | Model Monitoring | Observability | Performance Engineering | Python | Scalability | Security | Vector Databases | “as-code”
Education
N/A
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