8 of 8 Remote/Hybrid 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 ...

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 ...

experiment with new approaches and still care about getting models into production properly. What you could be working across Python PyTorch, TensorFlow or scikit-learn LLMs, RAG, agents and evaluation ML research and rapid prototyping MLOps and production ML pipelines Model deployment, monitoring and lifecycle tooling AWS, Docker ...

concepts, automated testing, continuous integration and continuous delivery, and production deployments. Commercial experience using key Python libraries for machine learning, such as Pandas, Scikit-learn and XGBoost. Proven development experience with cloud services, data stores and architectures, such as Vertex AI, BigQuery and Cloud Run. Hands-on experience ...

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 ...