15 of 15 Remote NLTK Jobs

Context embedding, Vector database technologies and Semantic Search techniques & tools. Proficiency in programming languages such as Python and experience with NLP libraries such as NLTK, spaCy, Transformers, Hugging Face, BERT and Gen AI frameworks like Llangchain. Llamaindex etc. Strong problem-solving skills and ability to handle complex NLP challenges. Excellent More ❯

Context embedding, Vector database technologies and Semantic Search techniques & tools. Proficiency in programming languages such as Python and experience with NLP libraries such as NLTK, spaCy, Transformers, Hugging Face, BERT and Gen AI frameworks like Llangchain. Llamaindex etc. Strong problem-solving skills and ability to handle complex NLP challenges. Excellent More ❯

or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. Familiarity with LLMs APIs More ❯

or another high-level language commonly used in machine learning. Experience with NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn, etc.). Demonstrated understanding of various techniques for extracting structured data from unstructured sources, indicating expertise in information retrieval. Familiarity with LLMs APIs More ❯

or another high-level language commonly used in machine learning. Expertise in NLP and Machine Learning frameworks and libraries (e.g., PyTorch, HuggingFace, LangChain, spaCy, NLTK, scikit-learn). Experience with information retrieval techniques and structured data extraction from unstructured sources. Hands-on experience with LLM APIs for pre-processing, fine More ❯

SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to communicate complex technical More ❯

SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to communicate complex technical More ❯

AI systems. Proficiency in Python and experience with ML libraries (e.g., scikit-learn, TensorFlow, PyTorch). Extensive experience with NLP techniques and libraries (e.g., NLTK, spaCy, Gensim, Transformers). Experience with version control systems (Git) Experience with AWS. Knowledge of MLOps practices and tools. If you have the above experience More ❯

machine learning models and working with APIs for data extraction. Experience with NLP including Text Classification, Sentiment Analysis, and Topic Modelling using tools like NLTK, BERT, and GCP NLP API. Fluent in English, both verbal and written What We Offer Competitive base salary 26 days holiday + bank holidays Contributory More ❯

and techniques into other systems. Are familiar with the Python data science stack through exposure to libraries such as Numpy , Scipy , Pandas, Dask , spaCy , NLTK, scikit-learn. Take pride in writing clean, reusable, maintainable and well-tested code. Demonstrate proficiency in automation, system monitoring, and cloud-native applications, with familiarity More ❯

and Matplotlib) for data manipulation, analysis, and visualisation Familiarity with advanced data science techniques, including machine learning (e.g., K-means), natural language processing (e.g., NLTK or spaCy), and data acquisition techniques (e.g., Selenium) is advantageous. Proficiency in producing detailed project documentation, including specifications, test plans, data quality checks, and validation More ❯

of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public More ❯

of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public More ❯

of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯

of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding communication More ❯