9 of 9 A/B Testing Jobs in Middlesex

Digital Marketing Manager (Marketo and Salesforce) Location: West London Hourly rate: £23.07p / h - £28.20p / h Hours: 9am to 5.30pm - hybrid Temporary - Immediate start required Looking for a Digital Marketing Manager with strong, hands-on Marketo and Salesforce experience to support campaign delivery and reporting … Experience supporting digital campaigns from a technical perspective Website optimisation and content experience, ideally WordPress : Landing page creation Forms A / B testing SEO and conversion rate improvement Data-driven mindset with the ability to analyse and optimise campaign performance Confident ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...

supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Lead the design and analysis of A / B tests and offline experiments to evaluate model efficacy and support continuous improvement. Cross-Functional Collaboration: Engage with multidisciplinary teams to align … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Advanced proficiency in Python and knowledge of ML libraries / frameworks (e.g., TensorFlow, PyTorch). Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe ...