51 to 75 of 323 scikit-learn Jobs in the UK

degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.Strong proficiency in Python or R, including libraries such as pandas, scikit‐learn, NumPy, TensorFlow, or PyTorch.Solid understanding of statistical analysis, hypothesis testing, and experimental design.Hands‐on experience applying a range of supervised and unsupervised machine learning ...

degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline. Strong proficiency in Python or R, including libraries such as pandas, scikit‐learn, NumPy, TensorFlow, or PyTorch. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Hands‐on experience applying a range of supervised ...

writing clean, efficient code for AI/ML solutions. Hands-on experience, through study, internships, or personal projects, with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Exposure to supporting the deployment of AI/ML models, working alongside engineering colleagues. Some exposure to generative AI concepts ...

writing clean, efficient code for AI/ML solutions. Hands-on experience, through study, internships, or personal projects, with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). Exposure to supporting the deployment of AI/ML models, working alongside engineering colleagues. Some exposure to generative AI concepts ...

team. What We're Looking For Strong commercial experience developing machine learning solutions using Python. Experience with frameworks such as: PyTorch TensorFlow Scikit-learn XGBoost Experience deploying ML solutions on AWS, including services such as SageMaker, Lambda, and S3. Strong understanding of MLOps tooling, including MLflow, Weights & Biases ...

Python or another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring ...

Python or another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring ...

Python or another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring ...

Python or another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring ...

Python or another modern programming language used for data science and machine learning development.Practical experience with machine learning frameworks and libraries such as scikit-learn, XGBoost, PyTorch, TensorFlow or equivalent.Experience across the end-to-end ML lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring ...

unstructured data, especially large-scale text or content datasets.Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib.The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills ...

unstructured data, especially large-scale text or content datasets. Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib. The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem ...

deploying AI applications in large scale production environments.Experience managing data science teams and couching team membersProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).Experience with generative models (transformers, GANs/VAEs; diffusion models a plus ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g. GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search and knowledge graphs. Actively contributes to open-source AI projects, research ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

applications in large scale production environments. Experience managing data science teams and couching team membersProficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn).Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK).Experience with generative models (transformers, GANs/VAEs; diffusion models a plus).Strong ...

with modern deep learning frameworks (e.g. PyTorch, TensorFlow), fine-tuning or distillation of LLMs (e.g., GPT, Llama, Claude, Gemini), machine learning libraries (e.g. scikit-learn, XGBoost). Experience with data storage for AI, vector databases, semantic search, and knowledge graphs. Contributions to open-source AI projects or research ...

context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

frameworks, context and memory management, and interoperability protocols such as MCPExperience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit-learn, NumPy, pandas, SciPy, and statsmodelsExperience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model and machine ...

leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management ...

/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools ...

object-oriented design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management. Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports. MLOps ...