Birmingham, West Midlands, West Midlands (County), United Kingdom Hybrid / WFH Options
Crimson
effectively. * Understanding of back-office technologies and their practical application in business environments. * Familiarity with agile development tools and platforms such as Jira, Confluence, Slack, GitHub, Azure DevOps, and Trello. * Ability to thrive in a fast-paced, dynamic work environment. * Experience with front-end JavaScript frameworks such as jQuery, React More ❯
requests from clients. Consulting with clients on their designs and projects, where necessary joining client calls to discuss issues and solutions, and communicating via Slack/Email with updates, to request information and to answer questions. Working with project managers to scope and estimate custom projects, working through solutions, and More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
doncaster, yorkshire and the humber, united kingdom
Inference Group
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
bradford, yorkshire and the humber, united kingdom
Inference Group
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
wakefield, yorkshire and the humber, united kingdom
Inference Group
a plus. Tooling and Tech: Familiarity with tools and platforms commonly used in data & AI projects, such as: version control (Git), collaboration tools (Confluence, Slack), ML lifecycle tools (MLflow, Kubeflow), and DevOps infrastructure (CI/CD pipelines, Terraform for infrastructure-as-code on cloud). Big Data & Analytics: Experience with More ❯
