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Senior Infrastructure Engineer - AI/ML

2 months ago
Germany
Senior
Infrastructure Engineer
DevOps and Infrastructure
AWS AWS CDK CircleCI CloudFormation Docker EC2 Generative AI GitHub Actions GitLab CI Grafana Kubernetes Linux LLM Machine Learning NLP OpenTelemetry Prometheus SageMaker Terraform
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Mitratech

Mitratech

Mitratech specializes in automating processes through innovative solutions and services in compliance, risk management, enterprise HR, and legal operations, empowering organizations to effectively manage risks and scale for future growth.

Professional Services
1K-5K
Founded 1987
$3M raised
View All Jobs 20

Description

  • Design, deploy, and maintain scalable and secure infrastructure for AI and ML workloads.
  • Build and maintain AWS cloud environments across compute, storage, networking, and security services.
  • Implement security best practices to protect AI systems, datasets, and environments.
  • Support and optimize AI/ML workloads across AWS services such as SageMaker, Bedrock, Batch, and Step Functions.
  • Develop and maintain infrastructure as code using Terraform, AWS CDK, and CloudFormation.
  • Manage containerized workloads and orchestration platforms, including GPU scheduling and scaling.
  • Set up and maintain monitoring and observability frameworks using CloudWatch and OpenTelemetry.
  • Build and manage CI/CD pipelines for infrastructure automation and ML/Gen AI deployments.
  • Collaborate with ML and Generative AI teams to scale models, optimize performance, and design prompt or inference pipelines.
  • Develop runbooks and SOPs for AI service deployment, troubleshooting, and performance optimization.

Requirements

  • Strong proficiency in Linux administration and systems-level troubleshooting.
  • Deep expertise in AWS cloud services across compute, storage, networking, and security domains.
  • Proficiency with container orchestration tools such as Kubernetes/EKS and infrastructure automation tools.
  • Hands-on experience with infrastructure as code tools such as Terraform, AWS CDK, or CloudFormation.
  • Familiarity with monitoring, logging, and observability tools such as Prometheus, Grafana, and 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.
  • Master’s degree in Machine Learning or Computer Science, with a preference for specialization in NLP.

Interested in this position?

Apply directly on the company website

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