1 to 25 of 167 Permanent scikit-learn Jobs in the UK

technical processes. Required Skills & Qualifications Classic Machine learning (Regression, predictive Analysis, Classification, Clustering) Machine learning Model Optimisation Strong proficiency in Python (NumPy, Pandas, Scikit-learn). Hands-on experience with Deep Learning frameworks: TensorFlow, PyTorch, or Keras. Experience in Natural Language Processing (NLP) and/or Computer Vision. ...

experience Strong SQL and experience working with large datasets Hands-on cloud experience (Azure, AWS or Snowflake) Expertise in machine learning frameworks (eg scikit-learn, XGBoost, PyTorch, TensorFlow) Strong knowledge of Generative AI, LLMs, RAG, embeddings and evaluation techniques MLOps experience (CI/CD, MLflow, containerisation, monitoring ...

production-grade analytical solutions. Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake). Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow). Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases). Strong ...

experience with LLMs, generative AI, NLP, or advanced modelling techniques. Proficiency in Python, SQL and modern data science libraries (e.g., PyTorch, TensorFlow, scikit-learn, HuggingFace). Experience mentoring or managing data scientists. Confident working in Agile environments with Git/version control. Strong communication skills, especially with ...

Python, R, or SQL, and experience with various data science and machine learning libraries.Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others.Experience with cloud-based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex AI, Azure ...

Python, R, or SQL, and experience with various data science and machine learning libraries. Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex ...

will collaborate with cross-functional teams to identify trends, patterns, and insights from large, complex datasets. Requirements Fluent Python, Pandas, Numpy, Matplotlib & Scikit-Learn 5+ consecutive years living in the UK Bachelor's or above in a STEM field (e.g., Maths, Physics, Data Science, Statistics, Computer Science) Ability ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

improving models and processes for better performance. Hands‐on development experience in Modelling. Advanced proficiency in Python (including libraries such as NumPy, Pandas, scikit‐learn, PyTorch/TensorFlow). Strong understanding of feature engineering, model selection, evaluation metrics, optimisation techniques and Gen AI. Ability to apply complex statistical ...

patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer ...

contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

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 ...

data scientists, promoting technical excellence and agile collaboration.Candidate ProfileRequired Skills and Experience:Expert-level fluency in Python, with experience in libraries such as scikit-learn, pandas, numpy, and Gurobi.Deep understanding of machine learning and operational research techniques (supervised, unsupervised learning, optimisation).Proven ability to deploy production-grade solutions ...

deploying AI applications in large scale production environments.Experience managing data science teams and coaching team members.Proficiency 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 ...

your technical approach as the problem becomes clearer. Your Skills & Expertise ML Fundamentals: Strong proficiency in Python and frameworks like PyTorch, TensorFlow, or Scikit-learn, with a deep understanding of NLP, deep learning, or reinforcement learning. Agentic AI: Hands‐on experience with modern AI orchestration tools such ...

Data Lake, Synapse Analytics, SQL Database). Programming skills in Python, R, or similar languages. Familiarity with ML frameworks and libraries (TensorFlow, PyTorch, Scikit‐learn). Experience with Azure DevOps, GitHub, or similar tools. Experience in Computer Vision for Optical Character Recognition (OCR) and object recognition. Knowledge ...

Data Lake, Synapse Analytics, SQL Database). Programming skills in Python, R, or similar languages. Familiarity with ML frameworks and libraries (TensorFlow, PyTorch, Scikit‐learn). Experience with Azure DevOps, GitHub, or similar tools. Experience in Computer Vision for Optical Character Recognition (OCR) and object recognition. Knowledge ...

Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes ...

Strong knowledge of machine learning and/or optimisation techniques (Regression, Tree methods, Clustering, Linear/Mixed-Integer Programming, Heuristics) Strong Python experience (scikit-learn, pandas, numpy, optimisation libraries) Experience building production-ready ML or optimisation solutions Solid understanding of CI/CD , Git version control, and cloud ...

deploying AI/ML solutions, with a strong focus on Microsoft Azure.Proficiency in Python and experience with relevant AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras).Demonstrated experience with Azure Machine Learning, including MLOps concepts, model registration, deployment (AKS, ACI), and monitoring.Hands-on experience with Azure ...

closely related field Strong foundations in machine learning, algorithms, and statistics Experience with Python and common ML libraries (e.g. TensorFlow, PyTorch, scikit-learn) Understanding of software engineering fundamentals and version control (e.g. Git) Ability to communicate technical ideas clearly to both technical and non-technical stakeholders Right ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

systems, personalisation, or deep learning is desirable but not essential. Solid Python skills and experience with ML libraries such as pandas, numpy, scipy, scikit-learn, TensorFlow or PyTorch. Experience working across cloud environments (GCP, AWS, or Azure) and analytics platforms such as Dataiku. Good understanding of MLOps practices ...

Engineer will have the following skills and experience: Strong Python and SQL experience, ideally with Databricks Experience with ML and LLM tools (e.g., scikit learn, XGBoost, PyTorch, TensorFlow, RAG, APIs) Comfortable with data engineering basics and MLOps practices Experience working with cloud platforms such as Azure ...