Core responsibilities
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Expand, maintain and optimize an existing On-Prem AI infrastructure in line with user needs and technical requirements
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Manage local servers, GPU workstations, and network drives
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Build and maintain Docker environments for AI tools, models and their deployment
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Resolve compatibility issues between containers, data Storage systems and web interfaces
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Develop internal RESTful APIs and secure network endpoints
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Collaborate with IT on Firewall management and secure access to AI systems
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Provide technical support to integrate open-source tools with local systems
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Modify internal data sources and create basic data extractions or interface elements
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Contribute ideas for infrastructure solutions that make AI models efficient and accessible to end users
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Support model improvement and the extension of AI functionality (if of interest)
Required skills
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Basic knowledge of Python (able to understand, debug and integrate scripts)
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Experience with containerization (Docker or equivalent tools)
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Experience with Linux and command-line tools
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Familiarity with building or using RESTful APIs
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Understanding of network settings and Firewall restrictions
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Basic knowledge of configuration formats (JSON, YAML, .env)
Assets (nice to have):
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Ability to work with or integrate SQL-like data sources
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Knowledge of GPU configuration (CUDA, drivers, resource management)
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Experience with simple web interfaces: front-end adjustments (HTML/CSS/JS) or back-end tools (e.g. Flask, Streamlit)
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Experience with CI/CD workflows (automated testing/deployment)
Relevant degrees:
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Master of science in
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Computer science / informatics
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Software engineering
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Applied computer science
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Artificial intelligence (with a technical focus)
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Professional bachelor in
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Applied computer science
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Electronics-ICT (with experience in software development or network infrastructure)
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