onsite
Junior DevOps / Machine Learning Engineer - Reply Deutschland SE
ML Engineer
Junior engineer driving cloud‑native solutions for data‑intensive ML workloads, designing scalable architectures on AWS, Azure, or GCP, and automating deployment pipelines to accelerate digital transformation.
About the role
Key Responsibilities
- Collaborate with clients to design and implement modern cloud strategies for data‑intensive applications, focusing on Machine Learning and AI workloads.
- Architect, deploy, and maintain scalable, secure cloud environments on AWS, Azure, GCP, or hybrid on‑premises infrastructures.
- Automate CI/CD pipelines, infrastructure as code, and monitoring solutions to ensure high availability and performance.
- Visualize architecture designs and performance metrics, translating technical concepts into clear business value.
- Participate in continuous improvement of DevOps practices, tooling, and security compliance.
Requirements
- Strong foundation in cloud platforms (AWS, Azure, GCP) and experience with IaC tools such as Terraform or CloudFormation.
- Hands‑on experience with containerization (Docker, Kubernetes) and CI/CD tooling (GitHub Actions, Jenkins, GitLab CI).
- Basic knowledge of Machine Learning workflows, data pipelines, and model deployment.
- Proficiency in scripting (Python, Bash) and understanding of networking, security, and monitoring concepts.
- Excellent communication skills and a proactive, collaborative mindset.
Skills
machine learningawsazuregcp