Description:
BASF is a leader in the chemical industry, driving innovation and sustainability through cuttingedge technology. We are currently seeking an experienced Cloud DevOps Engineer with a strong background in setting up and managing infrastructure for AI solutions to join our growing team of AI Enthusiasts. In this role, you will play a critical role in advancing our AI initiatives by creating a robust, secure, scalable, and efficient infrastructure for our large-scale AI solutions, preferably using Microsoft Azure Cloud services. If you are passionate about Large Language Models and AI in general, have a strong background in Cloud Engineering and enjoy working on cutting-edge topics, we want to hear from you!
Formula for Success: You Will…
- Designing, implementing, and maintaining cloud-based infrastructure for fine-tuning, (re)training and deploying large language models and other state-of-the-art AI models.
- Collaborating with AI researchers, data scientists, and other stakeholders to understand infrastructure requirements and optimize resource utilization.
- Automating and streamlining the deployment, monitoring, and scaling of AI models and AI applications within Microsoft Azure.
- Ensuring the security, reliability, and performance of the infrastructure, including data storage, compute resources, and network configurations.
- Continuously improving and optimizing the infrastructure to support the development and deployment of state-of-the-art AI models.
- Sharing your knowledge and expertise with colleagues and promoting a culture of innovation and excellence within the organization.
Qualifications
Ingredients for Success: What We Look for in You…
- Degree in Computer Science, Information Technology, or a related field.
- Excellent problem-solving, critical thinking, and communication skills.
- Strong experience with cloud platforms, preferably Microsoft Azure, including services such as Azure Machine Learning, Azure Kubernetes Service, and Azure Storage.
- Proficient in infrastructure as code (IAC) tools, such as Terraform or ARM templates, and configuration management tools like Ansible or Chef.
- Solid experience with script languages like Bash or Python..
- Solid understanding of DevOps principles, practices, and tools, including continuous integration, continuous deployment, and monitoring.
- Familiarity with containerization technologies such as Docker, and orchestration tools like Kubernetes or Docker Swarm.
- Continuous learning to keep up with the rapid technological developments in the field.
Bonus Points:
- Proven track record of successful infrastructure operations, preferably in an industrial or corporate research setting.
- Relevant certifications, such as Microsoft Certified: Azure DevOps Engineer Expert or Azure Administrator Associate.
- Experience with other cloud platforms, such as AWS or Google Cloud.
- Prior experience working with large language models or AI infrastructure.
- Knowledge of data engineering and preprocessing, including handling large datasets and ensuring data quality.
- Familiarity with AI ethics and responsible AI practices.