Senior Software Engineer - Infrastructure - AI / ML

Mitratech; München; Hybrid; EUR 70.000 - 90.000; Vollzeit

Zusammenfassung

A leading technology company in Munich is seeking a Cloud Engineer with deep expertise in AWS to support AI and ML workloads. In this role, you will design and maintain scalable infrastructure, implement security best practices, and collaborate with teams to ensure optimal performance. The ideal candidate holds a Master’s degree in Machine Learning or Computer Science, with proficiency in infrastructure automation tools and a solid understanding of AI concepts. This role emphasizes innovation and collaboration in a diverse work environment.

Qualifikationen

• Deep expertise in AWS cloud services with experience in compute, storage, networking, and security.
• Proficiency in container orchestration and infrastructure automation tools.
• Hands-on experience with IaC tools such as Terraform, AWS CDK, or CloudFormation.
• Familiar with monitoring, logging, and observability stacks like Prometheus and Grafana.
• Experience implementing CI/CD pipelines for automated deployment and testing.
• Understanding of AI/ML concepts including model deployment and scaling.
• Working knowledge of security best practices and compliance controls.
• Excellent collaboration and communication skills.

Aufgaben

• Design, deploy, and maintain infrastructure for AI and ML workloads.
• Build AWS cloud environments for compute, storage, and networking.
• Implement security best practices using AWS services.
• Support and optimize AI/ML workloads across AWS.
• Develop and maintain Infrastructure as Code using Terraform.
• Manage containerized workloads and orchestration platforms.
• Set up monitoring frameworks using CloudWatch.
• Build CI/CD pipelines for infrastructure automation.
• Collaborate with teams to scale models and optimize performance.
• Develop runbooks for service deployment and troubleshooting.

Kenntnisse

AWS cloud services expertise

Container orchestration (Kubernetes/EKS)

Infrastructure as Code tools (Terraform, AWS CDK, CloudFormation)

CI/CD pipeline implementation

AI/ML concepts understanding

Security best practices knowledge

Collaboration and communication skills

Ausbildung

Master’s degree in Machine Learning/Computer Science

Tools

Terraform

AWS CDK

CloudFormation

Docker

GitHub Actions

CircleCI

Prometheus

Grafana

OpenTelemetry

Jobbeschreibung

Responsibilities

• Design, deploy, and maintain scalable and secure infrastructure supporting AI and ML workloads.
• Build and maintain AWS cloud environments for compute (EC2, ECS / EKS, Lambda), storage (S3, EFS, FSx), and networking (VPC, Transit Gateway, PrivateLink, Route 53, load balancers).
• Implement security best practices using IAM, KMS, Secrets Manager, GuardDuty, and Security Hub.
• Support and optimize AI / ML workloads across AWS services (SageMaker, Bedrock, Batch, Step Functions).
• Develop and maintain Infrastructure as Code (IaC) using Terraform, AWS CDK, and CloudFormation.
• Manage containerized workloads and orchestration platforms (Docker, EKS, Fargate), including GPU scheduling and scaling.
• Set up and maintain monitoring and observability frameworks using CloudWatch and OpenTelemetry.
• Build and manage CI / CD pipelines (CircleCI, GitHub Actions, GitLab CI) for infrastructure automation and ML / Gen AI deployments.
• Collaborate with ML and Generative AI teams to scale models, optimize performance, and design efficient prompt or inference pipelines.
• Develop runbooks and SOPs for AI service deployment, troubleshooting, and performance optimization.
• Ensure security, compliance, and data protection across AI datasets and environments.

Requirements & Skills

• Deep expertise in AWS cloud services, with experience in compute, storage, networking, and security domains.
• Proficiency in container orchestration (Kubernetes / EKS) and infrastructure automation tools.
• Hands‑on experience with IaC tools such as Terraform, AWS CDK, or CloudFormation.
• Familiarity with monitoring, logging, and observability stacks (Prometheus, Grafana, OpenTelemetry).
• Experience implementing CI / CD pipelines for automated deployment and testing.
• Understanding of AI / ML concepts, including model deployment, inference scaling, and LLM performance tuning.
• Working knowledge of security best practices, IAM roles, encryption, and compliance controls.
• Excellent collaboration and communication skills to partner with ML engineers, data scientists, and product teams.

Education

• A Master’s degree in Machine Learning, Computer Science with a preference for specialization in the NLP domain.

We are an equal‑opportunity employer that values diversity at all levels. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, national origin, age, sexual orientation, gender identity, disability, or veteran status.