onsite
AI Configuration & Implementation Engineer - Liebherr-IT Services GmbH
Implementation Engineer
Design, configure, and deploy AI solutions, integrating machine‑learning models into production environments using Python, cloud services, and container orchestration.
About the role
Key Responsibilities
- Design and implement AI/ML pipelines from model development to production deployment.
- Configure and fine‑tune machine‑learning models using frameworks such as TensorFlow and PyTorch.
- Deploy AI services on cloud platforms (e.g., AWS) utilizing Docker and Kubernetes for scalability and reliability.
- Develop CI/CD workflows to automate testing, integration, and release of AI components.
- Collaborate with data scientists, software engineers, and product owners to translate business requirements into technical specifications.
- Monitor performance, troubleshoot issues, and continuously optimize AI solutions in live environments.
Requirements
- Strong proficiency in Python and experience with major ML frameworks (TensorFlow, PyTorch).
- Hands‑on experience deploying containerized applications using Docker and Kubernetes.
- Solid understanding of cloud services, preferably AWS, including IAM, S3, and EC2.
- Familiarity with CI/CD tools (Jenkins, GitLab CI, GitHub Actions) and version control (Git).
- Background in machine‑learning concepts, model training, evaluation, and optimization.
Skills
pythontensorflowpytorchawsdockerkubernetescicdmachine learning