1 to 25 of 114 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 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 ...

Node.js, Streamlit IDE experience: PyCharm, VS Code, JupyterLab, Eclipse, Notepad++, Sagemaker Studio, Azure ML Studio, Vertex AI Workbench Python Libraries NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras, PyTorch, PySpark, SpaCy, SciPy, NLTK, Statsmodels, Boto3, AzureSDK NLP & LLMs BERT, Word2Vec, Universal Sentence Encoder, NLTK, embeddings, fuzzy matching, topic modelling ...

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 ...

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. ...

learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science or machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Solid understanding of software engineering principles, including object-oriented programming, data structures, algorithms, and design patterns. Ability to quickly ...

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. ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

exposure to ML lifecycle. Hands-on experience building or maintaining ML workflows or pipelines. Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch. Familiarity with cloud platforms (especially Azure, AWS). Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes). Exposure ...

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 ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

experience delivering end-to-end ML or AI solutions into production environments* Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn* Experience working with LLMs, including prompt design, RAG, or fine-tuning* Experience building APIs and integrating AI systems into real products* Solid understanding ...

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 ...

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 ...

conversational AI, recommendation systems, optimisation, or marketing analytics. Deep understanding of ML fundamentals across the full lifecycle. Hands‐on experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...

will not be considered) Experience with CI/CD pipelines for ML/DL models Proficiency in Python and common ML libraries (e.g. Scikit-learn, TensorFlow, PyTorch) Experience with container technologies (Docker, Kubernetes) Consultancy or client-facing experience preferred Strong communication and stakeholder management skills Qualifications IT/ ...

preferred; AWS/Azure acceptable) Experience with GenAI/LLMs (commercial or serious hands-on experimentation) Strong Python and modern ML tooling (e.g. scikit-learn, XGBoost, TensorFlow or PyTorch) Clear interest in crypto/blockchain (commercial experience a plus, curiosity required) Responsibilities Build, train, and improve ML models ...

client in conjunction with this vacancy only. KEY SKILLS AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex ...

engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ...

Skills: Strong proficiency in programming languages such as Python, Java, C# or R. Experience with machine learning frameworks and libraries (e.g. TensorFlow, PyTorch, Scikit-learn). Familiarity with cloud platforms (AWS, Azure or Google Cloud) and MLOps practices. Knowledge of automation technologies including RPA platforms (e.g. UiPath ...

learn) Docker-based environments • Clear written communication skills Nice to have: • Experience with model training, fine-tuning, or ML frameworks (Python, PyTorch, scikit-learn) • Building and deploying ML data pipelines • AWS experience (ECS, S3, RDS, Elastic Beanstalk) • Redis and queue-based architectures • Third-party API integrations (Stripe ...

memory management. Experience with widely used tools in data science and machine learning. Developers should be somewhat familiar with libraries like NumPy, pandas, scikit-learn, and PyTorch. Proficiency in testing approaches and frameworks like pytest as well as automation tools like Github Actions or Travis CI for maintaining ...

engineers, and DevOps, with the freedom to shape how GenAI and ML are used across the platform. Tech stack: Python PyTorch or TensorFlow scikit-learn Spark Kafka Databricks LangChain and RAG-based GenAI systems Cloud-native Azure environment Important Details: Fully remote across ...