1 to 25 of 29 Remote/Hybrid CI/CD Jobs in South London

technical issues, ensuring minimal disruption to development processes.Optimize application performance and scalability through effective coding practices and system design.Implement and manage CI / CD pipelines to streamline the development and deployment process.Ensure the security and integrity of software applications through adherence to cybersecurity best practices. … Engineering, or a related field.2 years+ experience as a .Net Developer or similar role.Strong proficiency in the .Net Stack.Experience developing mobile applications in Xamarin / .Net MAUI / Flutter.Experience with software development methodologies such as Agile or Scrum.Excellent problem-solving skills and attention to detail.Strong communication and interpersonal ...

teams, and external partners. Ensure designs meet SLAs, security, compliance, and operational requirements. What You’ll Bring 8–10+ years in software engineering and / or solution architecture. Experience operating at Senior / Principal level in enterprise environments. Strong background in distributed, cloud‑native, and data‑intensive systems. … Deep AWS experience (essential). Strong data modelling and data architecture skills. Expertise in Java, Spring Boot, REST / event‑driven services; good knowledge of Angular / Node.js. Solid understanding of CI / CD, IaC (Terraform / CloudFormation), containers (Docker / ...

. 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 / ...

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 / ...