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.AI Infrastructure Architect(m/w/x)
Architecting and optimizing AI/ML infrastructure on cloud and on-premises compute. Several years of infrastructure engineering experience required. Coding, testing, configuring, deploying, monitoring, troubleshooting AI systems.
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Anforderungen
- Several years of infrastructure engineering experience
- Designing and optimizing AI/ML infrastructure
- Coding, testing, configuring, deploying, monitoring, troubleshooting AI systems
- Bachelor's Degree in Computer Science, Computer Engineering, or related field
- Practical experience in coding, building, monitoring, troubleshooting AI/ML models
- Selecting, designing infrastructure for deploying and running AI/ML models
- On-premise or public cloud AI/ML infrastructure deployment
- Strong understanding of AI and machine learning
- Strong understanding of computing infrastructure
- Preferred knowledge of AI infrastructure
- Proficiency in Python, Java, or C++
- Experience with data pipeline and workflow management tools
- Strong problem-solving skills
- Ability to work in a fast-paced environment
- Excellent communication skills
- Excellent collaboration skills
- Proven experience in AI/ML infrastructure engineering
- Experience on a hyperscaler platform for deploying large scale solutions
Aufgaben
- Architect and optimize AI and machine learning infrastructure
- Write and review code and deployment scripts
- Design and tune cloud and on-premises compute resources
- Deploy AI systems and models into production
- Build and optimize data pipelines for AI and ML workflows
- Optimize computational stack for performance, cost, power, and scalability
- Monitor AI systems and infrastructure health
- Perform AI monitoring to track model and system performance
- Troubleshoot and resolve complex issues across the stack
- Mentor junior engineers
- Contribute to architectural decisions
- Establish best practices
- Architect and configure compute resources
- Design and maintain CI/CD pipelines
- Lead container orchestration and model serving
- Evaluate and select tools and platforms
- Integrate AI models into enterprise systems
- Ensure interoperability, security, and regulatory compliance
- Lead root-cause analysis
- Define and document architecture standards
- Apply security, cost-efficiency, and scalability best practices
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