Applied AI Engineer – Devops
Company | Mistral AI |
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Location | Palo Alto, CA, USA |
Salary | $Not Provided – $Not Provided |
Type | Full-Time |
Degrees | Bachelor’s, Master’s |
Experience Level | Junior, Mid Level |
Requirements
- Fluent in English
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
- 2+ years of experience in a DevOps or Site Reliability Engineering role
- Experienced with deploying and managing AI-based products in production environments
- Fluent in Python
- Experience with containerization technologies such as Docker and Kubernetes
- Experience with CI/CD pipelines and automated deployment tools
- Deep understanding of cloud platforms (AWS, Azure, GCP) and on-premises infrastructure
- Experienced with infrastructure as code (IaC) tools such as Terraform or Ansible
- Strong communication skills with an ability to explain complex technical concepts in simple terms to technical and non-technical audiences
Responsibilities
- 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
- Deploying state-of-the-art AI applications from consumer products to industrial use cases, driving with customers a crucial technological transformation
- Collaborating with researchers, other AI engineers, and product engineers on complex customer projects involving deployment, scaling, and contributing to open-source codebases for tasks such as inference and fine-tuning
- Involved in pre-sales calls to understand potential clients’ needs, challenges, and aspirations, providing technical guidance on products and explaining Mistral technologies to various stakeholders
Preferred Qualifications
- 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