18 of 18 CI/CD Jobs in Middlesex

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

. Take end-to-end ownership of services, from development to production operations Optimising the performance of the application in the cloud environments Creating / improving automated pipelines that support our Continuous Delivery process Build, scale and maintain large scale cloud-based services Work closely with data scientists … scale datasets, with an understanding of scalability, fault tolerance, and performance considerations. Practical experience with modern software development practices, including automated CI / CD pipelines, containerisation technologies (e.g., Docker), and deploying applications to cloud environments (e.g., AWS or GCP). Ability to collaborate effectively across ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...

favourite teams, players, match context, and other signals while ensuring transparency, fairness, and appropriate use of data. Define advanced experimental designs, lead A / B testing, develop and maintain metrics and dashboards, establish robust MLOps practices, and own end-to-end productionisation from data ingestion through deployment and ongoing … extract insights from multi modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML / DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI / ...