Overview

Work within our clients machine learning team to deploy and optimize models for applications like low-latency speech recognition and large language models (LLMs). Initial focus will be on improving our clients speech recognition model’s training pipeline on multi-GPU systems to boost performance and quality.Responsibilities

Train and deploy state-of-the-art ML models.Apply optimization techniques (distillation, pruning, quantization).Enhance speech models with features such as diarization, multilingual support, and keyword boosting.Optimize models for low-latency inference on accelerators.Improve training workflows and GPU utilization.Use data augmentation to improve performance.Stay updated on ML research to guide strategy.Requirements

Master’s or PhD in a relevant field with strong ML foundations.Training ML models for production use.PyTorch or TensorFlow.Handling large datasets (multi-terabyte).Familiarity with Linux, version control, and CI/CD systems.Knowledge of model compression (e.g., reduced precision).

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