1 to 25 of 111 Remote/Hybrid Permanent scikit-learn Jobs

audiences, advocating for interpretability and audit best practices.Experience working with structured and unstructured datasets.Proficient in Python, leveraging key data science libraries (NumPy, Pandas, scikit-learn) and applying object-oriented programming principles to develop efficient, scalable solutionsHands-on experience experimenting with Generative AI (e.g. LangChain, Hugging Face, LlamaIndex).Experience ...

Data Scientist, Hands-on experience deploying ML models to production, not just research-level familiarity, Strong proficiency in Python (NumPy, pandas, scikit-learn, matplotlib, pytorch), Understanding of Windows or Linux software development platforms Excellent command of English – both written and spoken (international client communication, presentations), Expertise ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

/ML development, with practical experience across model development, testing and deployment. Experience with machine learning frameworks and libraries such as PyTorch, TensorFlow, scikit-learn, XGBoost or equivalent. Practical knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation, model evaluation and responsible ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

used for AI and data engineering, with hands-on experience building production-grade solutions.Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and practical implementation of model development and deployment.Working knowledge of Generative AI, including large language models, prompt engineering, retrieval-augmented generation and evaluation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

with hands-on experience developing, training, and deploying machine learning models.Practical experience with leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, XGBoost), including model selection, tuning, and evaluation.Experience implementing end-to-end machine learning workflows, including data preprocessing, feature engineering, model development, validation ...

another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative AI, LLMs ...

machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

data engineering, with hands-on experience building production-grade solutions. Experience with machine learning frameworks and tools (e.g., PyTorch, TensorFlow, scikit-learn) and end-to-end model development and deployment. Working knowledge of Generative AI techniques, including large language models, prompt engineering, retrieval-augmented generation and evaluation methods. ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

work on projects independently and own deliverables. Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn). Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.). ...

Community of Practice. Experience Required Essential Strong Python programming and hands-on experience with core ML/AI libraries (for example scikit-learn, TensorFlow, PyTorch). Practical experience developing, training and evaluating machine learning, NLP and predictive models. Experience deploying AI/ML in the cloud, particularly Microsoft ...

coaching junior data scientists/analysts. Experience in reviewing code and documentation to a high standard. Experience in using Python (pandas, numpy, scikit-learn). End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data (text, numerical ...