3 days ago
Vienna, AustriaSenior
Responsibilities
- Write, review, and debug code, scripts, and infrastructure-as-code for AI infrastructure, automation, and tooling.
- Architect, configure, and provision cloud and on-premises compute resources, including GPU clusters and distributed training environments.
- Design and maintain deployment automation and CI/CD pipelines for reliable releases of AI systems, models, and applications.
- Deploy AI systems, models, and data pipelines into production and establish repeatable deployment practices.
- Lead container orchestration and model serving using Docker, Kubernetes, and model deployment frameworks.
- Optimize computational infrastructure for performance, power, cost, utilization, and scalability.
- Evaluate and select infrastructure tools, frameworks, and platforms and contribute to the infrastructure roadmap.
- Integrate AI models and systems with enterprise systems while supporting interoperability, security, and regulatory compliance.
- Own AI monitoring and infrastructure health across InfraOps and MLOps, tracking performance, reliability, and utilization.
- Troubleshoot complex issues across hardware, networking, software, and models and lead root-cause analysis.
- Mentor junior engineers, lead code reviews, and provide technical direction.
- Define and document architecture standards, processes, procedures, and infrastructure best practices.
Requirements
- Bachelor's degree in computer science, computer engineering, or a related engineering field.
- Practical experience coding, building, monitoring, and troubleshooting applications using AI/ML models and designing infrastructure to deploy and run them on-premises or in public clouds.
- Strong understanding of artificial intelligence and machine learning.
- Strong understanding of computing infrastructure, preferably including AI infrastructure.
- Proficiency in programming languages such as Python, Java, or C++.
- Experience with data pipeline and workflow management tools such as Apache Airflow and Kubeflow.
- Proven experience in AI/ML infrastructure engineering or related roles on a hyperscaler platform for deploying large-scale solutions.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Excellent communication and collaboration skills.
Benefits
- Flexible working models, including home office.
- Access to more than 30,000 training opportunities covering professional and soft skills.
- Certifications and learning platforms.
- Flexible working hours, a modern work environment, and additional benefits.
- Annual gross salary starts at €53,600 depending on qualifications and experience.
Tech Stack
Categories
About Accenture
Accenture is a global professional services firm providing management consulting, systems integration and technology, cybersecurity, and business process outsourcing for enterprises and governments. It operates a services-driven model delivering projects and managed services, often with major cloud and software partners, across industries worldwide. Headquartered in Dublin and publicly traded on the NYSE (ACN), it originated as Andersen Consulting and adopted the Accenture name in 2001.