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Mistral AI

Reseach Engineer, Full Stack

Palo AltofulltimemidAdded today

About this role

Mistral seeks a Research Engineer to bridge internal teams and customers by developing full-stack AI applications that integrate cutting-edge models into enterprise software. You'll collaborate across researchers, engineers, and product teams to design scalable solutions and guide production deployment.

What you'll do

  • Collaborate with researchers and engineers to integrate AI models into customer software products
  • Design, develop, and maintain scalable full-stack applications with seamless front-end and back-end integration
  • Develop complex use cases with internal stakeholders and guide production integration
  • Provide technical guidance to explain complex concepts to technical and non-technical audiences
  • Work with product and science teams to improve product capabilities based on internal feedback
  • Facilitate adoption of Mistral products among internal teams and address technical challenges

What they're looking for

  • Python and TypeScript
  • Front-end frameworks (React, NextJS, or VueJS)
  • Back-end technologies (NodeJS)
  • Full-stack development and software architecture
  • Design patterns, data structures, and algorithms
  • LLM/GenAI models
  • Technical communication and stakeholder collaboration
  • Software development principles

Benefits

  • Healthcare coverage
  • Parental leave
  • Retirement plans
  • Relocation support
  • Wellness programs
  • Meal and transportation allowances
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Mistral AI

Mistral AI builds large-scale machine learning systems and open-weight AI models, supported by infrastructure powering petabyte-scale HPC clusters and enterprise AI platforms. The company is hiring Systems Engineers, Research Engineers, Site Reliability Engineers, and Applied AI Engineers to scale training infrastructure, optimize data systems, ensure platform reliability, and drive customer adoption across industries.

Website
mistral.ai
View all jobs at Mistral AI

Likely interview questions

  • Describe a complex AI model integration you've built—what were the technical challenges and how did you solve them?
  • How do you approach designing a full-stack system to balance scalability, robustness, and maintainability?
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