Mistral AI에서 DevOps/SRE 역량을 갖춘 Applied AI Engineer를 채용합니다. 고객의 AI 도입을 지원하고 인프라를 구축하는 핵심 역할을 수행하며, 5년 이상의 DevOps 경력과 Python, Kubernetes, 클라우드 플랫폼에 대한 깊은 이해가 필수입니다. 한국어와 영어 능통자를 찾고 있으며, 기술적 문제 해결과 고객 커뮤니케이션 능력이 중요합니다.
At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
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 France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.
Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.
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.
• 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.
• You are fluent in English and Korean
• You hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field
• You have 5+ 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
