Staff Machine Learning Engineer - LLM Quantization & Deployment
Tasks
- Analyze numerical errors accuracy regressions performance tradeoffs
- Benchmark VLA performance
- Build model export calibration benchmarking validation deployment pipelines
- Collaborate with training infrastructure team for QAT and model distillation
- Curate evaluation datasets
- Develop PTQ QAT orchestration workflows
- Develop VLA inference models
- Ensure numerical consistency with training models
- Implement PTQ QAT mixed precision inference
- Perform latency analysis with in vehicle software team
- Productionize LLM quantization methods
- Triage field testing simulation issues
Perks/Benefits
Skills/Tech-stack
Benchmarking | Calibration | Data evaluation | FP4 | INT8 | Inference Optimization | Language Models | Large Language Models | Latency analysis | Lower Bit Quantization | MLIR | Machine Learning | Mixed Precision | Model Distillation | Model Quantization | Model Serving | Model export | Numerical analysis | ONNX Runtime | Post-training | Post-training Quantization | PyTorch | Python | Quantization aware training | Systems engineering | TVM | TensorRT-LLM | Transformer | VLLM | Validation
Education
Regions
Countries
States
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