About Mistral
Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.
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 Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.
The Role
Embedded directly in a product team as search, chat, documents, or audio, you'll improve AI-powered features through rigorous evaluation, prompt and orchestration design, and rapid experimentation. You'll own your domain's AI quality end-to-end: define what "good" looks like, measure it, run experiments, and ship what works. Work with Science to deliver measurable improvements to quality, latency, safety, and reliability.
What You Will Do
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Design and run evaluations for your product area: reference tests, heuristics, model-graded checks tailored to search relevance, chat quality, document understanding, or audio performance.
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Define and track metrics that matter: task success, helpfulness, hallucination proxies, safety flags, latency, cost.
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Own prompt and orchestration design: write, test, and iterate on prompts and system prompts as a core part of your work.
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Run A/B tests on prompts, models, and configurations; analyze results; make rollout or rollback decisions from data.
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Set up observability for LLM calls: structured logging, tracing, dashboards, alerts.
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Operate model releases: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection.
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Improve core behaviors in your product area, whether that's memory policies, intent classification, routing, tool-call reliability, or retrieval quality.
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Create templates and documentation so other teams can author evals and ship safely.
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Partner with Science to diagnose regressions and lead post-mortems.
What We're Looking For
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3-4 years of experience; backgrounds that fit well include ML engineers moving closer to product, or software engineers with real AI/ML production experience.
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Strong TypeScript or Python skills - we have both tracks depending on team fit.
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Production LLM experience: prompts, tool/function calling, system prompts.
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Hands-on with evals and A/B testing; you can design metrics, not just run them.
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Comfortable implementing directly in product code, not only notebooks.
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Observability experience: logging, tracing, dashboards, alerting.
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Product mindset: form hypotheses, run experiments, interpret results, ship.
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Clear communication, autonomous, and oriented toward production impact over experimentation for its own sake.
It would be ideal if you also have:
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Safety systems experience: moderation, PII handling/redaction, guardrails.
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Release operations: canary/shadowing, automated rollbacks, experiment platforms.
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Prior work on search ranking, chat systems, document AI, or audio ML features.
What We Offer
We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.
For the most up-to-date details on benefits available in your location, please refer to our Benefits page.
Privacy Policy
Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy.
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