Machine Learning Engineer - TRAE USDS

Design, train, and fine-tune large language models to support advanced code generation and reasoning capabilities.
Build efficient, stable, and scalable model training and evaluation pipelines.
Collaborate with infrastructure and product teams to deploy and monitor models on GPU clusters.
Continuously optimize models for latency, throughput, and accuracy.
Stay up-to-date with cutting-edge techniques in large-model optimization and inference acceleration.
Qualifications include a degree in CS/EE/Math, strong ML fundamentals, PyTorch or TensorFlow, Python and C++/CUDA, distributed training experience, and quantization or pruning skills; Master's and 3+ years are preferred.