WISE Campaign
Job description At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. Our Compute Platform Engineering team builds a first in class platform of toolchains and workflows that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking over abstractions that encompass Cloud and High Performance Computing (HPC). This metadata forward, CI/CD driven platform represents and enables the entire application and analysis lifecycle including interactive development and explorations (notebooks), large scale batch processing, observability and production application deployments. Key Responsibilities Design, build and operate tools, services, workflows that deliver high value through solutions to key business problems. Develop key components of a hybrid on prem/cloud compute platform for both interactive and scalable batch computing and establish processes and workflows to transition existing HPC users and teams to this platform. Manage code driven environment, applications and container/image builds as well as CI/CD driven application deployments. Consult science users on application scalability to PBs of data, incorporating deep understanding of software engineering, algorithms and underlying hardware infrastructure. Optimize design and execution of complex solutions within large scale distributed computing environments. Produce well engineered software, including automated test suites, technical documentation, and operational strategy. Ensure consistent application of platform abstractions to maintain quality and consistency with respect to logging and lineage. Adhere to coding best practices, participate in code reviews and partner to improve team standards. Follow QMS framework and CI/CD best practices, guiding continual improvements. Basic Qualifications Bachelor's degree in Data Engineering, Computer Science, Software Engineering or related field. 4+ years of professional experience. Experience with Python. Experience with Cloud. Experience with High Performance Compute (HPC). Preferred Qualifications Knowledge and use of at least one common programming language: Python, Go, C++, Scala, Java, including toolchains for documentation, testing and operations/observability. Expertise in modern software development tools and ways of working (e.g., git/GitHub, devops tools, metrics, monitoring). Cloud expertise (AWS, Google Cloud, Azure), including infrastructure as code tools and scalable compute technologies such as Google Batch and Vertex. Experience with CI/CD implementations using git and a common CI/CD stack (Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab). Expertise with Docker, Kubernetes and the larger CNCF ecosystem, including Helm. Experience with low level application build tools (make, CMake) and automated build systems such as Spack or EasyBuild. Experience in workflow orchestration with tools such as Argo Workflow, Airflow, Nextflow, Snakemake, VisTrails, or Cromwell. Experience with application performance tuning and optimization, including parallel and distributed computing paradigms and communication libraries such as MPI, OpenMP, Gloo. Demonstrated excellence with agile software development environments using Jira and Confluence. Familiarity with tools, techniques and optimizations in the high performance applications space, including engagement with the open source community. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
Job description At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization represents a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. Our Compute Platform Engineering team builds a first in class platform of toolchains and workflows that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking over abstractions that encompass Cloud and High Performance Computing (HPC). This metadata forward, CI/CD driven platform represents and enables the entire application and analysis lifecycle including interactive development and explorations (notebooks), large scale batch processing, observability and production application deployments. Key Responsibilities Design, build and operate tools, services, workflows that deliver high value through solutions to key business problems. Develop key components of a hybrid on prem/cloud compute platform for both interactive and scalable batch computing and establish processes and workflows to transition existing HPC users and teams to this platform. Manage code driven environment, applications and container/image builds as well as CI/CD driven application deployments. Consult science users on application scalability to PBs of data, incorporating deep understanding of software engineering, algorithms and underlying hardware infrastructure. Optimize design and execution of complex solutions within large scale distributed computing environments. Produce well engineered software, including automated test suites, technical documentation, and operational strategy. Ensure consistent application of platform abstractions to maintain quality and consistency with respect to logging and lineage. Adhere to coding best practices, participate in code reviews and partner to improve team standards. Follow QMS framework and CI/CD best practices, guiding continual improvements. Basic Qualifications Bachelor's degree in Data Engineering, Computer Science, Software Engineering or related field. 4+ years of professional experience. Experience with Python. Experience with Cloud. Experience with High Performance Compute (HPC). Preferred Qualifications Knowledge and use of at least one common programming language: Python, Go, C++, Scala, Java, including toolchains for documentation, testing and operations/observability. Expertise in modern software development tools and ways of working (e.g., git/GitHub, devops tools, metrics, monitoring). Cloud expertise (AWS, Google Cloud, Azure), including infrastructure as code tools and scalable compute technologies such as Google Batch and Vertex. Experience with CI/CD implementations using git and a common CI/CD stack (Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab). Expertise with Docker, Kubernetes and the larger CNCF ecosystem, including Helm. Experience with low level application build tools (make, CMake) and automated build systems such as Spack or EasyBuild. Experience in workflow orchestration with tools such as Argo Workflow, Airflow, Nextflow, Snakemake, VisTrails, or Cromwell. Experience with application performance tuning and optimization, including parallel and distributed computing paradigms and communication libraries such as MPI, OpenMP, Gloo. Demonstrated excellence with agile software development environments using Jira and Confluence. Familiarity with tools, techniques and optimizations in the high performance applications space, including engagement with the open source community. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.
WISE Campaign
Job description Site Name: London The Stanley Building Posted Date: Jun 8 2026 Overview At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization is a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. Team and Role We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward building a next-generation, metadata- and automation-driven data experience for GSK's scientists, engineers, and decision makers, providing best-in-class AI/ML, aggressively engineering our data at scale. The Compute Platform Engineering team is building a first-in-class platform of toolchains and workflows that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking over abstractions that encompass Cloud and High-Performance Computing. This metadata-forward, CI/CD-driven platform represents and enables the entire application and analysis lifecycle including interactive development, large-scale batch processing, observability and production application deployments. Key Responsibilities Design, build and operate tools, services, workflows that deliver high value solving key business problems Develop key components of a hybrid on prem/cloud compute platform for interactive and scalable batch computing and establish processes and workflows to transition existing HPC users and teams to this platform Develop code driven environments, applications, and container/image builds as well as CI/CD driven application deployments Consult science users on application scalability to petabytes of data, having deep understanding of software engineering, algorithms and infrastructure impact on performance Optimize design and execution of complex solutions within large scale distributed computing environments Produce well engineered software, including automated test suites, documentation and operational strategy Ensure consistent application of platform abstractions for logging and lineage quality and consistency Apply coding best practices, participate in code reviews and improve team standards Adhere to QMS framework and CI/CD best practices, guiding improvements to them and ways of working Provide leadership to team members helping others complete tasks properly Basic Qualifications Bachelor's degree in data engineering, Computer Science, Software Engineering or related discipline 6+ years of professional experience Experience with Python Experience with Cloud Experience with High Performance Compute (HPC) Preferred Qualifications Deep knowledge of at least one common programming language (Python, C++, Java) including documentation, testing, and operations tools Expertise in modern software development tools and workflows (Git, GitHub, DevOps tools, metrics, monitoring) Deep cloud expertise (AWS, Google Cloud, Azure) including infrastructure-as-code and scalable compute technologies (Google Batch, Vertex, etc.) Experience with CI/CD implementations using Git and a common CI/CD stack (Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab) Expertise with Docker, Kubernetes and the CNCF ecosystem, including Helm Experience with low level application build tools (make, CMake) and automated build systems (Spack, EasyBuild) Experience with workflow orchestration tools (Argo, Airflow, Nextflow, Snakemake, VisTrails, Cromwell) Experience with application performance tuning and optimization in parallel and distributed computing, MPI, OpenMP, Gloo and underlying systems Demonstrated excellence in agile environments using Jira and Confluence Deep familiarity with optimizations in high performance application space and open source community engagement Equal Opportunity Employer Statement GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information, military service or any basis prohibited under federal, state or local law.
Job description Site Name: London The Stanley Building Posted Date: Jun 8 2026 Overview At GSK, we want to supercharge our data capability to better understand our patients and accelerate our ability to discover vaccines and medicines. The Onyx Research Data Platform organization is a major investment by GSK R&D and Digital & Tech, designed to deliver a step-change in our ability to leverage data, knowledge, and prediction to find new medicines. Team and Role We are a full-stack shop consisting of product and portfolio leadership, data engineering, infrastructure and DevOps, data / metadata / knowledge platforms, and AI/ML and analysis platforms, all geared toward building a next-generation, metadata- and automation-driven data experience for GSK's scientists, engineers, and decision makers, providing best-in-class AI/ML, aggressively engineering our data at scale. The Compute Platform Engineering team is building a first-in-class platform of toolchains and workflows that accelerate application development, scale up computational experiments, and integrate all computation with project metadata, logs, experiment configuration and performance tracking over abstractions that encompass Cloud and High-Performance Computing. This metadata-forward, CI/CD-driven platform represents and enables the entire application and analysis lifecycle including interactive development, large-scale batch processing, observability and production application deployments. Key Responsibilities Design, build and operate tools, services, workflows that deliver high value solving key business problems Develop key components of a hybrid on prem/cloud compute platform for interactive and scalable batch computing and establish processes and workflows to transition existing HPC users and teams to this platform Develop code driven environments, applications, and container/image builds as well as CI/CD driven application deployments Consult science users on application scalability to petabytes of data, having deep understanding of software engineering, algorithms and infrastructure impact on performance Optimize design and execution of complex solutions within large scale distributed computing environments Produce well engineered software, including automated test suites, documentation and operational strategy Ensure consistent application of platform abstractions for logging and lineage quality and consistency Apply coding best practices, participate in code reviews and improve team standards Adhere to QMS framework and CI/CD best practices, guiding improvements to them and ways of working Provide leadership to team members helping others complete tasks properly Basic Qualifications Bachelor's degree in data engineering, Computer Science, Software Engineering or related discipline 6+ years of professional experience Experience with Python Experience with Cloud Experience with High Performance Compute (HPC) Preferred Qualifications Deep knowledge of at least one common programming language (Python, C++, Java) including documentation, testing, and operations tools Expertise in modern software development tools and workflows (Git, GitHub, DevOps tools, metrics, monitoring) Deep cloud expertise (AWS, Google Cloud, Azure) including infrastructure-as-code and scalable compute technologies (Google Batch, Vertex, etc.) Experience with CI/CD implementations using Git and a common CI/CD stack (Azure DevOps, CloudBuild, Jenkins, CircleCI, GitLab) Expertise with Docker, Kubernetes and the CNCF ecosystem, including Helm Experience with low level application build tools (make, CMake) and automated build systems (Spack, EasyBuild) Experience with workflow orchestration tools (Argo, Airflow, Nextflow, Snakemake, VisTrails, Cromwell) Experience with application performance tuning and optimization in parallel and distributed computing, MPI, OpenMP, Gloo and underlying systems Demonstrated excellence in agile environments using Jira and Confluence Deep familiarity with optimizations in high performance application space and open source community engagement Equal Opportunity Employer Statement GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information, military service or any basis prohibited under federal, state or local law.
