9 NLTK Jobs

architecting and managing the cloud infrastructure, using Terraform > Mentoring less experienced engineers Senior ML Learning Engineer the environment: > Python - advanced features, NumPy, keras, pandas, NLTK, scikit, SpaCy > Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) > Strong more »

exciting new role will see you specifying, designing, developing and testing in Python. ML Learning Engineer – the environment: Python - advanced features, NumPy, keras, pandas, NLTK, scikit, SpaCy Machine Learning – NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data more »

exciting new role will see you specifying, designing, developing and testing in Python. ML Learning Engineer the environment: Python - advanced features, NumPy, keras, pandas, NLTK, scikit, SpaCy Machine Learning NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data more »

exciting new role will see you specifying, designing, developing and testing in Python. ML Learning Engineer – the environment: Python - advanced features, NumPy, keras, pandas, NLTK, scikit, SpaCy Machine Learning – NLP, ML algos, Hugging Face, large language models (LLMs), Retrieval Augmented Generation), learning algorithms, neural networks, ML frameworks (TensorFlow, PyTorch) Data more »

etc.) Proficiency with deep learning packages (such as PyTorch, Jax, or TensorFlow) Experience with ML/LLM Software packages (e.g. HuggingFace, wandb, numpy, matplotlib, NLTK, etc.) Good problem-solving and communication skills Ability to work in a dynamic and fast-paced environment Ability to demonstrate passion and knowledge in terms more »

set): Python, R, Data Science, Machine Learning, Artificial Intelligence, PyTorch, TensorFlow, Scikit-learn, Pandas, Identity Providers, oAuth2, Tableau, SQL, MS SQL Server, PostgreSQL, Spacy, NLTK, FlairNLP, Fast API, Django/REST Framework, REST APIs, RDF/XML, JSON-LD, IIIF, UI/UX and DevOps. All Data Scientist can look more »

machine learning methodologies and algorithms Expertise in popular data science platforms such as Alteryx and Python, including libraries and frameworks like NumPy, SciPy, Pandas, NLTK, TensorFlow, PyTorch, and Airflow Strong understanding of statistical analysis, encompassing distributions, statistical testing, regression, and other techniques Experience handling unstructured data sets Familiarity with software more »

in either Python/Typescript Knowledge of natural language processing (NLP) and computer vision techniques for advanced automation and generative AI applications.(e.g SpaCy, NLTK, or Hugging Face). Experience supporting digital platforms, including Integrations, Release Management, Regression Testing, Integrations, Data Obfuscation, etc. Experience scaling an “API-Ecosystem”, designing, and more »

AI, math, probability, statistics and algorithms Ability to write robust code in Python Familiarity with machine learning frameworks (like PyTorch) and libraries (like Natural Language Toolkit) Experience with AWS (ideally with Bedrock and/or SageMaker) Experience with agile development (Scrum) is a plus Experience working on a remote team more »