55 geprüfte Jobs in der KI-Infrastruktur

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You’ll be responsible for onboarding customers on our products, providing guidance on deployment and integration, and ensuring the best production setup from the low-level GPU stack up to infrastructure, back-end and front-end interfaces.

• You’ll work on deploying state-of-the-art AI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation.
• You’ll work in collaboration with our researchers, other AI engineers, and product engineers on our most complex customer projects involving deployment, scaling, and contributing to our open-source codebases for tasks such as inference and fine-tuning.
• You’ll be involved in pre-sales calls to understand potential clients needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. About you
• You are fluent in English
• You hold a Bachelor s or Master s degree in Computer Science, Engineering, or a related field
• You have 2+ years of experience in a DevOps or Site Reliability Engineering role
• You re experienced with deploying and managing AI-based products in production environments
• You are fluent in Python
• You have experience with containerization technologies such as Docker and Kubernetes
• You have experience with CI/CD pipelines and automated deployment tools
• You have deep understanding of cloud platforms (AWS, Azure, GCP) and on-premises infrastructure
• You are experienced with infrastructure as code (IaC) tools such as Terraform or Ansible
• You hold strong communication skills with an ability to explain complex technical concepts in simple terms to technical and non-technical audiences Ideally you have:
• Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager
• Familiarity with AI frameworks such as PyTorch or TensorFlow
• Contributions to open-source projects, particularly in the space of DevOps or AI By applying, you agree to our Applicant Privacy Policy.

Das wird geboten

vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks. For the most up-to-date details on benefits available in your location, please refer to our Benefits page. Privacy Policy Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.

Zur Position

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms. We are a dynamic, collaborative team passionate about AI and its potential to transform society.

Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

About The Job Mistral AI is seeking an Applied AI Engineer focused on DevOps to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. Applied AI Engineers, ML Infra at Mistral AI work directly with customers to quickly understand their greatest challenges and design and implement AI solutions. In this role, you’ll apply your problem-solving ability, creativity, and technical skills to help organizations use AI to drive real impact in the world.

You’ll have the opportunity to gain rare insight into and contribute to some of the most important industries and institutions globally! Applied AI Engineers, ML Infra responsibilities look similar to those of a startup CTO: you’ll work in small teams and own end-to-end execution of high-stakes projects. A day might span discussing architecture with fellow engineers, wrangling massive-scale data, coding a custom web app, speaking with customer executives, or establishing a strategy for the Applied Engineering team.