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Software Developer

Guidant Global

Cheltenham

On-site

GBP 80,000 - 100,000

20 days ago

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Job summary

An established industry player is seeking a skilled Software Developer to enhance their analytic capabilities. This contract role involves working with cutting-edge technologies such as Docker, Jenkins, and Kubernetes to manage infrastructure and automate workflows. You'll be responsible for building pipelines for machine learning models, creating user-friendly applications, and streamlining data processing. If you have a passion for technology and a knack for problem-solving, this is a fantastic opportunity to contribute to innovative projects and make a significant impact in a dynamic environment.

Qualifications

  • Erfahrung in der Verwaltung von Docker und Jenkins-Pipelines.
  • Kenntnisse in der Entwicklung von Automatisierungsskripten und UI-Anwendungen.

Responsibilities

  • Bau von Pipelines zur Bereitstellung und Ausführung von ML-Modellen.
  • Automatisierung manueller Arbeitsabläufe und Integration von Datenquellen.

Skills

Docker Management

Jenkins Pipelines

Kubernetes Deployments

Apache NiFi Development

Application Development

Job description

Software Developer

£512 - £600 per day inside IR35

This contract role will require you to hold valid DV clearance.

Location: based in Gloucestershire, London or Manchester.

As we look to improve our analytic capability, we need to enhance our underlying technologies, stacks, and tools. Do you have the skills and interest in any of the following topics?

  1. Infrastructure Management: e.g. Docker Management, Jenkins Pipelines, Kubernetes Deployments, overall VM Management application, and tool deployment.
  2. Automations: e.g. Deployments of tools and scripts to data pipelines to process data on arrival from various partners, Apache NiFi Development.
  3. UI and Application Development: We have a set of requirements that provide user and system interfaces to bring all of our information to our users more effectively.

The types of work we are currently involved in consist of:

  1. Building the pipelines to deploy and run ML models on data ingest.
  2. Creating applications to merge queries across multiple tools and environments.
  3. Automating manual workflows.
  4. Applying and deploying new models.
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