Machine Learning Engineer

Job Description

Craft and refine advanced NLP systems utilizing state-of-the-art Python libraries such as NLTK, SpaCy, Hugging Faces Transformers, TextBlob, Gensim,Langchain, and scikit-learn. Analyze, preprocess, and interpret large datasets, applying techniques like sentiment analysis, topic modeling, and syntactic parsing. Develop and maintain machine learning models with TensorFlow or PyTorch, leveraging Pythons robust support for these frameworks. Innovate and implement new features for Document AI that leverage Azure Form Recognizers custom models and prebuilt options for specific domains. Who you are: Bachelor s or Master s in Computer Science, Computational Linguistics, Artificial Intelligence, or related field. Minimum of 2 years of experience in designing and implementing NLP solutions in a production environment. Experience in Python NLP libraries (NLTK, SpaCy, Hugging Face Transformers, Snorkal, Gensim) and frameworks (TensorFlow, PyTorch). Demonstrated skill in developing high-performance algorithms for NLP tasks, such as text classification, language modelling LLMs, or named entity recognition, using Python. Knowledge of state-of-the-art NLP models like BERT, GPT, T5 etc. Strong analytical and problem-solving skills. Experience in deploying Python-based NLP solutions in cloud environments (AWS ,GCP, Azure). Familiarity with Python web frameworks (e.g., Flask, Django) for deploying NLP applications as RESTful APIs. Background in deploying NLP models in a microservices architecture. Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes). Experience with CI/CD pipelines and test-driven development

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