MLOps Engineer
Tasks
- Build autoscaling and capacity management
- Design and operate model serving platforms
- Develop deployment workflows with canary releases and rollback
- Document operational procedures and tuning guidance
- Drive end-to-end observability
- Implement caching and prompt deduplication
- Implement multi tenant routing and rate limiting
- Implement security controls for serving layer
- Integrate model serving with API gateways and observability
- Optimize inference performance
- Provide incident response and reliability improvements
- Support new model releases and capability rollouts
- Tune GPU utilization and memory management
Perks/Benefits
Skills/Tech-stack
API Gateway | Abuse detection | Automated rollback | Autoscaling | C++ | Caching | Canary Releases | Capacity Planning | Cloud Platforms | Content Filtering | Distributed Systems | GPU Architecture | Go | KV cache | Kubernetes | LLM Inference | Memory Management | Metrics | Observability | Performance Engineering | Prompt Deduplication | Python | Request Signing | Rust | Shadow testing | Structured Logging | TensorRT-LLM | Tracing | VLLM
Education
Roles
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