ML Platform Engineer
Tasks
- Build deployment workflows canary shadow rollback
- Build inference request routing
- Design model serving platforms
- Develop autoscaling and capacity management
- Document operational procedures and performance tuning
- Implement continuous batching and caching
- Implement multi tenant routing rate limiting QoS
- Implement security controls request signing content filtering abuse detection
- Integrate observability metrics tracing logging
- Operate incident response for AI services
- Optimize GPU utilization and memory management
Perks/Benefits
- N/A
Skills/Tech-stack
API Gateway | Abuse detection | Automated rollback | Autoscaling | Batching | C++ | Caching | Canary Release | Capacity Planning | Content Filtering | Distributed Systems | GPU Architecture | GPU Utilization | Go | Identity Management | Incident Response | Inference | KV cache | Kubernetes | LLM | Memory Management | Metrics | Observability | Performance Engineering | Python | Quality of Service | Rate Limiting | Request Routing | Request Signing | Rust | Security | Shadow testing | Structured Logging | TensorRT-LLM | Tracing | VLLM
Education
Roles
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