Production AI Engineer: LLM Prompts & Evaluation

Mistral

Paris

Sur place

EUR 70 000 - 110 000

Plein temps

14 jours+
Générateur de candidature

Une candidature conçue pour ce poste — un CV et une lettre de motivation personnalisés qui correspondent à l’offre.

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Avantages offerts par ce poste

Healthcare coverage
Relocation support
Retirement plans
Wellness programmes
Meal & transport allowances

Résumé du poste

Mistral in Paris seeks an AI/ML engineer focused on product-quality improvements across search, chat, documents, or audio features. You will own end‑to‑end evaluation, define what good looks like, measure it, run experiments, and ship reliable enhancements.

You’ll design prompts and orchestration, run A/B tests, monitor observability, and contribute to model releases with canary/shadow strategies and rollback criteria.

Qualifications

  • 3–4 years of experience in ML engineering or AI‑driven software.
  • Strong TypeScript or Python skills.
  • Production experience with LLMs, prompts, and tool calls.
  • Hands-on with evals and A/B testing and metrics design.
  • Comfort implementing in production code and observability practices.

Responsabilités

  • Design and run evaluations for your product area.
  • Define and track metrics that matter.
  • Own prompt and orchestration design.
  • Run A/B tests and analyze results.
  • Set up observability for LLM calls.
  • Operate model releases with canary and rollback criteria.
  • Improve core behaviours like routing and retrieval quality.
  • Create templates and documentation for evals.
  • Partner with Science to diagnose regressions and post‑mortems.

Connaissances

TypeScript
Python
Production LLM
Eval & AB testing
Observability
Product mindset
Communication

Description du poste

Mistral in Paris seeks an AI/ML engineer focused on product-quality improvements across search, chat, documents, or audio features. You will own end‑to‑end evaluation, define what good looks like, measure it, run experiments, and ship reliable enhancements.

You’ll design prompts and orchestration, run A/B tests, monitor observability, and contribute to model releases with canary/shadow strategies and rollback criteria.

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