AI Platform Engineer
Tasks
- Build benchmarking and metrics tooling
- Define performance and availability SLOs
- Implement inference optimizations
- Improve monitoring tracing and alerting
- Optimize inference runtimes and servers
- Optimize vLLM and Triton components
- Own production model inference
- Participate in incident response and postmortems
- Perform root cause analysis for bottlenecks
- Reduce latency and increase throughput
- Scale inference across GPU fleets
- Serve production LLMs
Perks/Benefits
- N/A
Skills/Tech-stack
Alerting | CUDA | Capacity Planning | Continuous batching | Distributed tracing | GPU Architecture | Go | Incident Response | KV cache | Kernel programming | Monitoring | Performance Profiling | PyTorch | Python | Quantization | Rust | SGLang | Speculative decoding | TensorRT | VLLM
Education
N/A
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