15 of 15 scikit-learn Jobs in the North of England

customers. Machine Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

customers. Machine Learning, predictive modelling and applied AI, developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

customers. Machine Learning, predictive modelling and applied AI , developing, evaluating and operationalising models using state-of-the-art libraries and frameworks such as scikit-learn, TensorFlow, PyTorch and XGBoost, helping tackle complex challenges including in areas like fraud prevention, credit risk management and customer personalisation. Generative AI, Large ...

machine learning, or statistical modeling, Practical experience with ML model deployment (on cloud or on-premise), Solid programming skills in Python (NumPy, pandas, scikit-learn, matplotlib, PyTorch or TensorFlow), Understanding of Windows or Linux software development platforms Good understanding of statistics and data preparation, Working knowledge ...

following areas would be highly beneficial: - Machine Learning and AI Engineering- Generative AI and Large Language Models- Prompt engineering and context engineering- scikit-learn, PyTorch or TensorFlow- LangChain or similar AI frameworks- Cloud data platforms and services across AWS, Azure or GCP- Data warehouses and modern data platforms ...

client projects Requirements 5+ years of experience in machine learning engineering or applied ML research Strong proficiency in Python, PyTorch or TensorFlow, and Scikit-learn Experience deploying ML models at scale using Docker, Kubernetes, or serverless Deep understanding of ML fundamentals: optimisation, regularisation, evaluation metrics Experience with cloud ...

Experience with Cloud AI services such as Azure ML, AWS SageMaker, GCP Vertex AI. Hands-on experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time ...

retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise a data scientist’s work, reason about what a model needs from the data ...

retraining, and monitoring for drift and model degradation (MLflow, SageMaker, Databricks ML, Vertex AI or comparable) Are comfortable with ML frameworks such as scikit-learn, PySpark MLlib, or PyTorch/TensorFlow, enough to productionise a data scientist’s work, reason about what a model needs from the data ...

Desirable Experience Machine Learning model development and training. LLMs, transformers, RAG and Agentic AI. LangChain, LangGraph or similar AI orchestration frameworks. PyTorch, TensorFlow, Scikit-learn or Hugging Face. Vector databases, embeddings and model evaluation. NLP, Computer Vision or multimodal AI. Edge AI, AI safety, security or explainability. Experience ...

making trade-offs made, unsuitable approaches rejected, risks identified and commercially credible solutions developed. Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (e.g., Azure AI, AWS SageMaker, Google Cloud AI) Experience with Private cloud platforms (HPE Private AI, Nvidia AI Enterprise ...

such as statistical modelling, supervised and unsupervised learning, deep learning, transformers, Generative AI or Agentic AI. Experience across areas such as PyTorch, TensorFlow, scikit-learn, Hugging Face, cloud platforms, MLOps, computer vision, NLP, geospatial data or multimodal AI would also be of interest, although candidates are not expected ...

closely related field . Essential Application Demonstrable programming skills in Python, including common data science/machine learning libraries (eg pandas, scikit-learn or PyTorch/JAX). Essential Application/interview Working knowledge of core machine learning methods (eg regression, classification, clustering). Essential Application/interview ...

Proven success in leading the design, development, and deployment of sophisticated predictive models. Expertise in Python/R and ML frameworks, such as scikit-learn, TensorFlow, or PyTorch, Proven ability to design and implement complex machine learning solutions and guiding best practice. Deep understanding of statistical analysis ...

Raffles, Singapore | Posted on 04/06/2026 Experience working with ML platforms such as CML, SparkMLlib, and Python ML libraries (scikit‐learn, XGBoost), including modeldeployment. Design and develop highly scalable, Real time systemsusing Hadoop ecosystem components(Iceberg, Spark, Ozone, Trino, Hive,Ranger, Kafka, Flink and Nifi ...