The day-to-day

• Craft and refine advanced NLP systems utilizing state-of-the-art Python libraries such as NLTK, SpaCy, Hugging Face's Transformers, TextBlob, Gensim, Langchain, and scikit-learn.
• Lead initiatives to 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 Python's robust support for these frameworks.
• Innovate and implement new features for Document AI that leverage Azure Form Recognizer's custom models and prebuilt options for specific domains.
• Guide the team in adopting best practices for NLP development in Python, including the use of virtual environments, package management.
• Mentor junior engineers and advocate for Pythonic approaches to software design and implementation in the NLP domain.

Who you are:

• Bachelor’s or Master’s in Computer Science, Computational Linguistics, Artificial Intelligence, or related field.
• Minimum of 5 years of experience in designing and implementing NLP solutions in a production environment.
• Expertise 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