1 to 25 of 32 Remote scikit-learn Jobs in the UK excluding London

Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

TensorFlow and PyTorch. Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, TensorFlow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on More ❯

them to strong results. Experienced in engaging with non-technical partners 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. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with More ❯

them to strong results. Experienced in 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 etc. Knowledge of Langchain More ❯

accuracy. Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud More ❯

data science or a quantitative academic field. Strong programming background; must be able to quickly become fluent in Python . Proficiency with key data science libraries (NumPy, Pandas, Scikit-Learn) and experience with deep learning frameworks (TensorFlow, PyTorch, or Caffe). Strong mathematical and statistical skills. Broad knowledge of core data science techniques, such as: Supervised/unsupervised More ❯

discussions and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. More ❯

discussions and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. More ❯

discussions and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. More ❯

or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices More ❯

or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices More ❯

or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering practices More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations and reports. Familiarity with Git and collaborative development workflows. Good written More ❯

large databases and data warehouses. You'll be proficient in Python, R, or other relevant programming languages and have Experience with machine learning libraries and frameworks (e.g., TensorFlow, Scikit-learn, PyTorch). With a background in data mining and pattern recognition you'll be an expert in statistical modelling, predictive analytics and regression techniques. An industry certification in More ❯

processing to sequential data and decision-making post PhD. Experience in software development for proof of concept in Python. Experience with machine and deep learning frameworks: TensorFlow, PyTorch, scikit-learn, etc. Domains of Particular Interest RF communications and CEMA Electronic or Electromagnetic Warfare (EW) Tracking and sensor data fusion Radar signal processing Acoustic data processing (including sonar) Distributed More ❯

and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

Modelling Approaches: Machine learning, optimisation, stochastic and agent-based models About You Experience in the energy sector - markets, trading, forecasting, etc. Strong Python skills with machine learning frameworks (scikit-learn, TensorFlow, PyTorch). Knowledge of GitHub/Azure DevOps and SQL advantageous. Excellent communicator, able to explain technical concepts to non-technical audiences. Degree (or equivalent experience) in More ❯

algorithms, and frameworks . Proficiency in programming languages (Python, R, C/C++, Java) and secure coding practices. Hands-on experience with ML/LLM frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Expertise in DevOps/CI/CD security and cloud-native architectures (containers, Kubernetes, Git). Strong knowledge of AI/ML-specific security vulnerabilities (adversarial More ❯

Europe,andinternationally. RequiredExperience Strongknowledgeofdatamodelling,machinelearning,and/oradvanceddataanalytics. Demonstrabletrackrecordofdeliveringdataanalyticsprojectsaspartofateam. Hands-onexperiencewithcollaborativesoftwaredevelopmentandversioncontrol(preferablyGit). FamiliaritywithAgile/SCRUMmethodologies. Exposuretopre-engagementactivitiessuchasprojectscoping,technicalfeasibilityanalysis,orprototypedevelopment. Comfortablecontributingtotechnicaldiscussionsandimplementingsolutionsdefinedbyprojectleads. DesirableExperience StrongPythonexpertise. ExperiencewithGNU/Linuxenvironments. FamiliaritywithkeydatascienceandMLframeworks(e.g.,scikit-learn,PyTorch,TensorFlow,XGBoost,HuggingFace). Experienceinnaturallanguageprocessing,tabulardataanalysis,orcomputervision. SQLproficiency. Exposuretocontainerisation(Docker,Kubernetes)andcloud-nativearchitectures. ExperiencewithCI/CD,automatedtesting,anditerativeproductdevelopment. Knowledgeofgraphdatabasesandgraphanalysis. Benefits Ourclientoffersanexcitingandsupportiveenvironmentwithastrongfocusonemployeewellbeingandcareerdevelopment.Benefitsinclude: 35daysannualleave(includingpublicholidays)plusupto10daysunpaidleave. Flexibleworkingarrangementsaroundcorehours. Privatehealthinsuranceandpensionscheme. Contributiontogymmembership. More ❯

Senior Machine Learning Engineer £90000-110000 GBP Hybrid WORKING Location: Gloucester, South West - United Kingdom Type: Permanent Senior Machine Learning Engineer - Defence & Security £90,000 - £110,000 | Gloucester Area | Hybrid (2-3 days on-site as required) To be eligible More ❯