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We are looking for a Machine Learning Engineer with a focus on Natural Language Processing (NLP) and Automatic Speech Recognition (ASR).
This role is ideal for someone with solid ML fundamentals who has hands-on experience with real-world data and is interested in working with text and speech-based systems.
Requirements:
— 2–4+ years of experience.
— Strong understanding of how models perform and behave in production environments.
— Experience with GPU-based training is a strong plus.
— Python: Strong proficiency.
— Data Science Stack: Hands-on experience with NumPy, Pandas, and scikit-learn.
— DL Frameworks: Experience with PyTorch (preferred) or TensorFlow.
— English level: Upper-Intermediate or higher.
ML & Mathematics:
— Solid understanding of linear algebra, probability, and statistics.
— Practical knowledge of classic algorithms (regression, classification, clustering).
— Deep understanding of performance metrics (Accuracy, Precision, Recall, F1) and the Bias-Variance tradeoff.
NLP:
Experience with:
— Tokenization, lemmatization
— TF-IDF, Bag of Words, n-grams
Understanding of Transformers architecture
Experience with:
— Hugging Face Transformers
Practical experience with:
— Text classification
— Named Entity Recognition (NER)
— Fine-tuning pre-trained models.
ASR (Automatic Speech Recognition):
Understanding of:
— Spectrograms
— MFCC
Experience with audio processing:
— librosa, torchaudio
Familiarity with:
— CTC (Connectionist Temporal Classification)
— Seq2Seq + Attention
— Wav2Vec 2.0
— WhisperX
Practical experience with:
— Speech-to-text pipelines;
— Audio preprocessing and cleaning;
— Data augmentation (noise, speed, etc.)
Familiarity with metrics:
— WER (Word Error Rate)
— PER (Phoneme Error Rate).
Nice to have:
— Production deployment.
— Working with noisy data.
We offer:
— Interesting tasks and projects.
— Competitive salary.
— Remote work.
— Annual paid vacation: 20 days.
— Paid sick leaves: 10 days.
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