AI Engineer - Model Performance
Tasks
- Benchmark quantization strategies
- Build fine tuning pipelines
- Debug production inference quality regressions
- Evaluate model serving frameworks
- Optimize GPU selection and batching strategies
- Optimize model inference performance
- Perform GPU profiling and performance analysis
- Reduce model serving cost and latency
Perks/Benefits
Skills/Tech-stack
Attention Backend | Audio Processing | Batching | CUDA | CUDA graph | Cost modeling | DPO | Data Preparation | FP8 | GPU Profiling | JSONL | KV cache | LLM Inference | Learning Rate | Learning Rate Scheduling | LoRA | Modal | Model Serving | Multimodal Models | Performance Engineering | Python | QLoRA | Quantization | Ray Serve | SFT | SGLang | Speculative decoding | TensorRT-LLM | Torch compile | Training Data Preparation | Training data | VLLM
Education
N/A
Roles
AI | AI Engineer | Engineer | Model Performance Engineer | Performance Engineer
Regions
Countries
States
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