MLOps Engineer
Tasks
- Build autoscaling and capacity management
- Design model serving platforms
- Develop deployment workflows
- Document operational procedures
- Drive end-to-end observability
- Implement caching and prompt deduplication
- Implement routing and rate limiting
- Implement security controls
- Integrate with API gateways and identity systems
- Optimize inference performance
- Perform incident response and reliability improvements
- Support new model releases
- Tune GPU utilization and memory management
Perks/Benefits
- N/A
Skills/Tech-stack
API Gateway | Automated rollback | Autoscaling | C++ | CUDA | Caching | Canary Releases | Data logging | Distributed Systems | GPU | GPU Utilization | Go | Identity Management | Incident Response | KV cache | Kubernetes | Memory Management | Metrics | Observability | Prompt Deduplication | Python | Quality of Service | Rate Limiting | Rust | Shadow testing | Structured Data Logging | Structured Logging | Structured data | TensorRT-LLM | Tracing | VLLM
Education
Roles
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