AI Evaluation Platform Research Engineer

Mistral; Paris; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Mistral is seeking a Research Engineer for the Eval Platform to build scalable evaluation infrastructure. You will ensure results are reliable, reproducible and fast, enabling researchers to compare models and benchmarks effectively.

You will collaborate with researchers to support agentic and tool-using models, run large-scale GPU evaluations, and develop APIs and dashboards so results are accessible and trustworthy.

Qualifications

• Master's or PhD in Computer Science, or equivalent experience.
• 4+ years building production-grade software, ideally large-scale ML codebases or distributed systems.
• Excellent Python and strong software-design instincts: testing, code review, CI/CD.
• Experience running workloads on GPU clusters (Slurm, Kubernetes, Ray or similar).
• Familiarity with LLM inference and evaluation.
• A product mindset: researchers are your users.
• Self-starter, low-ego, collaborative.

Responsibilities

• Build systems that keep eval results reproducible and comparable over time, as models, benchmarks and code evolve.
• Run evaluations at scale across our GPU clusters, from model serving to scoring.
• Make eval results easy to access, explore and trust, through APIs and dashboards that researchers use every day.
• Catch broken or noisy evals before they mislead research decisions.
• Support evaluation of agentic, multi-turn and tool-using models.
• Work closely with researchers to turn new evaluation needs into robust, shared tooling.

Skills

Python

Software design

Testing

Code review

CI/CD

LLM eval

Product mindset

Self-starter

Collaborative

GPU workloads

Education

Master's or PhD in Computer Science, or equivalent experience.

Tools

Slurm

Kubernetes

Ray

vLLM

SGLang

Job description

Mistral is seeking a Research Engineer for the Eval Platform to build scalable evaluation infrastructure. You will ensure results are reliable, reproducible and fast, enabling researchers to compare models and benchmarks effectively.

You will collaborate with researchers to support agentic and tool-using models, run large-scale GPU evaluations, and develop APIs and dashboards so results are accessible and trustworthy.