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Spektrum
Scraped fromLinkedin4 days ago
Data Science

AI Technologist

Ai/MlMachine LearningDeep LearningReinforcement LearningPythonJavaC#JavaScriptTensorflowPytorchDockerKubernetesAWSAzureREST APIMicroservices
Work Type
Remote
Job Type
Location
The Hague
Salary
Not specified

About the Position

Spektrum has a wide range of exciting opportunities supporting apex purchasers like NATO, UN, and National Governments with specialized services in aerospace and defense. We are looking for personnel to join our team and support key client projects, including advanced cybersecurity, command and control systems, and more.

Responsibilities

  • Leading the identification and scoping of AI/ML use cases applicable to (T)BMD fire-control coordination and IAMD operational challenges.
  • Reviewing existing NIAG SG300 reports and TBMD simulation data to establish baseline knowledge and identify relevant datasets.
  • Designing a baseline data architecture and methodological framework for the responsible use of advanced AI technologies within the BMD domain.
  • Conducting feasibility studies on emerging AI/ML computational techniques and assessing their potential operational benefit for identified use cases.
  • Developing and evaluating AI/ML software prototypes and demonstrators for selected BMD use cases at NATO UNCLASSIFIED level.
  • Preparing and providing subject matter (BMD AI) briefings, expert reports, and feasibility study documentation related to the project work.
  • Developing and documenting a responsible AI framework aligned to NATO's Principles of Responsible AI Use.

Requirements

  • More than 10 years of professional experience in software engineering, AI/ML system development, or related technical disciplines.
  • Hands-on expertise in AI/ML frameworks and tools, including PyTorch, TensorFlow, scikit-learn, or equivalent.
  • Strong proficiency in software development using one or more of the following languages: Python, Java, C#/.NET, JavaScript/TypeScript.
  • Experience in the design and development of distributed software architectures, including microservices, RESTful APIs, cloud-native components, and containerised deployment using Docker and Kubernetes.
  • Demonstrated ability to design, implement, and evaluate AI/ML software prototypes and demonstrators.
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AI Technologist