26 to 50 of 226 scikit-learn Jobs in the UK

into applications Requirements ✓ Degree in Computer Science, Data Science, Mathematics or equivalent experience ✓ Strong proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn) ✓ Experience building and deploying production ML models ✓ Understanding of supervised and unsupervised learning techniques ✓ Experience with cloud platforms (AWS, Azure or GCP) ✓ Strong problem ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models in production, including model monitoring and real-time inference Experience in scientific computing with ...

models that drive measurable business value. Technical Proficiency: Strong expertise in Python and SQL. Deep familiarity with the Python data stack (pandas, NumPy, scikit-learn) and standard ML frameworks (such as PyTorch, XGBoost, or LightGBM). Engineering Rigor: Proven ability to build for production. Experience working in cloud ...

applications in large scale production environments. Experience managing data science teams and couching 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 ...

like Python for model development, experimentation, and integration with OpenAI API. Experience with machine learning frameworks, libraries, and APIs, such as TensorFlow, PyTorch, Scikit-learn, and OpenAI API. Experience with cloud computing platforms (e.g., AWS, Azure, or Google Cloud Platform), containerization technologies (e.g., Docker and Kubernetes), and microservices ...

bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling ...

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 ...

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/ ...

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/ ...

Learning, Statistics, Data Science, Physics, Computer Science, or a related field, or equivalent education and industry experience. Advanced Python proficiency with Pandas, NumPy, scikit-learn, and PyTorch or TensorFlow; SQL and practical data preparation skills. Strong statistics, experimental design, hypothesis testing, ML validation, and applied classification, regression, ranking ...

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 ...

lifecycle expertise: feature engineering, model training, evaluation and production deployment, including MLOps, monitoring and drift detection. Practical knowledge of ML frameworks (e.g. scikit‐learn, PyTorch, XGBoost) and cloud‐native ML services (SageMaker, Azure ML, Vertex AI). Architecture and delivery of scalable cloud data and AI platforms ...

Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models in production, including model monitoring and real-time inference Experience in scientific computing with ...

foundational model systems and frameworks/best practices for building agents. Experience using Python and common data science libraries such as pandas, scikit-learn, NumPy and visualisation frameworks. Strong SQL skills with experience querying and transforming large datasets, ideally using platforms such as BigQuery, Snowflake, or similar ...

stay on top of emerging tools, especially in GenAI and agentic AI We're looking for: Advanced Python, including NumPy, Pandas and Scikit-learn, with hands-on experience building, training and deploying ML models Strong practical knowledge of GenAI, including prompt engineering, LLM optimisation, multimodal AI and agentic ...

language processing (NLP) and its applications. Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects. Working with other team members to productionize end-to-end AI/ML solutions. Engaging in research ...

product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

across multiple ML domains, including: Forecasting/Time-Series Modelling Regression Classification Gradient Boosting models (e.g. XGBoost, LightGBM) Strong Python skills (Pandas, NumPy, scikit-learn, PyTorch) Experience with model evaluation, performance monitoring, and accuracy metrics Version control (Git) Experience working with cloud environments (Azure preferred, AWS/ ...

identify opportunities to improve business efficiency through intelligent automation. Skills & Experience Strong Python programming skills with experience using libraries such as Pandas, NumPy, Scikit-learn, XGBoost or LightGBM, and Plotly, Rust, Typescript, Python or Matplotlib. Experience developing machine learning models for prediction, optimisation or classification. Strong SQL skills ...

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 ...

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 ...

broad familiarity with common algorithms and architectures. Strong Python (pandas, NumPy, etc.) and SQL skills Comfortable with the standard ML toolkit: Git, Docker, scikit-learn, PyTorch or TensorFlow, and ML pipelines. Hands-on experience with text data and relevant Natural Language Processing techniques. Solid experience with cloud technologies ...

managing a data science team. Proficiency in programming languages such as Python, R, and SQL.Strong experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).Experience with cloud platforms (e.g., AWS, GCP, Azure) and distributed computing (e.g., Spark).Solid understanding of statistical analysis and hypothesis testing methods. Strong ...

Hands‐on experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity ...

machine learning, AI engineering, or data science Hands‐on experience with production ML systems Strong Python skills and experience with tools such as: scikit‐learn, PyTorch, TensorFlow Pandas, NumPy Hugging Face/generative AI tooling Understanding of MLOps, cloud platforms (AWS, Azure, GCP), and SQL A passion ...