Applied AI Engineer, ML Infrastructure Engineer / Devops - EMEA

Mistral
Munich, Paris, Amsterdam, London, Switzerland
Workplace: OnsiteFull timeFunction: DevOps, Cloud & InfrastructureExperience: 2+ yearsEducation: mastersSkills: ["Communication","Problem-solving","Collaboration"]

Own end-to-end deployment and integration of Mistral AI products for customers, guiding production setups from GPU stack through infrastructure and front/back-end interfaces. Deploy and scale state-of-the-art AI applications across consumer and industrial use cases while collaborating with researchers and product engineers on inference and fine-tuning. Support pre-sales technical calls and contribute to open-source codebases. Partner with customers to drive real, high-stakes technical transformation.

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FursaFursa
Mistral
Mistral
1 month ago

Applied AI Engineer, ML Infrastructure Engineer / Devops - EMEA

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live
Reposted: similar role first listed 1 month ago

Job Summary

Own end-to-end deployment and integration of Mistral AI products for customers, guiding production setups from GPU stack through infrastructure and front/back-end interfaces. Deploy and scale state-of-the-art AI applications across consumer and industrial use cases while collaborating with researchers and product engineers on inference and fine-tuning. Support pre-sales technical calls and contribute to open-source codebases. Partner with customers to drive real, high-stakes technical transformation.
Location: Munich, Paris, Amsterdam, London, Switzerland
Workplace: Onsite
Employment Type: Full time
Job Function: DevOps, Cloud & Infrastructure
Seniority: Mid level

Key Responsibilities

  • •Onboard customers by guiding product deployment and integration, and ensuring production setup from GPU stack to infrastructure and interfaces
  • •Deploy and scale state-of-the-art AI applications across consumer and industrial use cases
  • •Collaborate with researchers and engineers on complex customer projects, including deployment, scaling, inference, and fine-tuning
  • •Contribute to open-source codebases related to inference and fine-tuning
  • •Participate in pre-sales calls to understand client needs and provide technical guidance to stakeholders

Pay and Benefits

Perks:Health InsuranceParental LeaveRetirementRelocation SupportWellness StipendMeal AllowanceCommuter Benefits

Key Requirements

  • •2+ years of experience in a DevOps or Site Reliability Engineering role
  • •Experience deploying and managing AI-based products in production environments
  • •Fluency in Python
  • •Experience with containerization technologies such as Docker and Kubernetes
  • •Experience with CI/CD pipelines, infrastructure as code (Terraform or Ansible), and cloud platforms (AWS, Azure, GCP)
Experience:2+ yearsAIDevOpsSite Reliability EngineeringProduction deploymentsCloud infrastructure
Education:Master's in Computer Science, Engineering, or a related field
Skills:CommunicationProblem-solvingCollaboration
Languages:English
Tech Stack:PythonDevOpsDockerKubernetesCI/CDAWSAzureGCPTerraformAnsibleInfrastructure as codePyTorchTensorFlowInferenceFine-tuning

Company Brief

Mistral
Develops state-of-the-art large language models and AI systems, offering models and developer tools for natural language understanding, generation, and enterprise AI integrations. Focuses on open research and production-ready model deployments.
Industry: AI & Machine Learning
Company Size: Medium (51 to 250 employees)
Growth: Early Stage Startup
Funding: Seed
Headquarters: Paris, France
Founded: 2023
WebsiteLinkedIn