ML Engineer
DKhardware
11 апреля 2025
Кишинев
С опытом
Полный день
Не имеет значение
На территории работодателя
Be part of a DK Hardware team that unleashes the power of leading-edge technologies to help improve e-commerce processes in hardware world.
Your role in our mission
Development and enhancement of nlp models for text analysis.
Creation of data processing methods to improve text analysis accuracy.
Evaluation and tuning of models using standard metrics for real-world tasks.
Fine-tuning and optimization of neural networks for classification, structuring, sorting, and automated document processing.
Analysis and implementation of open-source AI solutions for practical applications.
What we’re looking for
Python: fundamental programming language.
PyTorch: neural network training and inference for NLP.
Hugging Face Transformers (ELECTRA, BERT, and etc.)
SimpleTransformers: convenient library for transformer model management.
Pandas and NumPy: data preparation, processing, and analysis.
Scikit-learn: model evaluation metrics (ROC-AUC, PR-AUC, confusion matrix).
Tokenizers (Hugging Face), NLTK: tokenization and text processing.
Matplotlib, Seaborn, tensorboardX: visualization and model performance logging.
CUDA/Conda: GPU acceleration for model training and inference.
Pickle: saving and loading models and data.
AdamW, ReduceLROnPlateau: model optimization and learning rate scheduling.
Different NLP techniques for classification
Docker, Kubernetes, Slurm: application containerization and orchestration.
TensorBoard, wandb: monitoring, logging, and visualization of model performance.
Education
Bachelor degree in Engineering of Science in required
Your role in our mission
Development and enhancement of nlp models for text analysis.
Creation of data processing methods to improve text analysis accuracy.
Evaluation and tuning of models using standard metrics for real-world tasks.
Fine-tuning and optimization of neural networks for classification, structuring, sorting, and automated document processing.
Analysis and implementation of open-source AI solutions for practical applications.
What we’re looking for
Python: fundamental programming language.
PyTorch: neural network training and inference for NLP.
Hugging Face Transformers (ELECTRA, BERT, and etc.)
SimpleTransformers: convenient library for transformer model management.
Pandas and NumPy: data preparation, processing, and analysis.
Scikit-learn: model evaluation metrics (ROC-AUC, PR-AUC, confusion matrix).
Tokenizers (Hugging Face), NLTK: tokenization and text processing.
Matplotlib, Seaborn, tensorboardX: visualization and model performance logging.
CUDA/Conda: GPU acceleration for model training and inference.
Pickle: saving and loading models and data.
AdamW, ReduceLROnPlateau: model optimization and learning rate scheduling.
Different NLP techniques for classification
Docker, Kubernetes, Slurm: application containerization and orchestration.
TensorBoard, wandb: monitoring, logging, and visualization of model performance.
Education
Bachelor degree in Engineering of Science in required
Адрес:
Кишинев
Дата актуализации:
11 апреля 2025
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