Principal Machine Learning Engineer
Tasks
- Architect and build large scale machine learning systems
- Architect inference systems for latency throughput cost and reliability
- Design and maintain training data systems
- Design reproducible high performance training pipelines
- Implement evaluation pipelines for performance robustness safety and bias
- Integrate ML systems into backend mobile and desktop products
- Monitor debug and resolve production ML issues
- Own production ML deployment with GPU optimization and scaling
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Arrow | Apache Spark | Bias Mitigation | DPO | Deep learning | DeepSpeed | Diffusion Models | Distributed Training | Distributed inference | FSDP | FasterTransformer | GPU Optimization | Inference latency | Inference latency optimization | JAX | Latency optimization | Machine Learning | Megatron | Memory efficiency | Mixed Precision | Model Evaluation | Multimodal Models | ORPO | PPO | PyTorch | Quantization | RLHF | Ray | Safety evaluation | Synthetic data | TensorRT-LLM | Throughput Optimization | Transformers | VLLM | Zero
Education
N/A
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