채용
복지 및 혜택
•Unlimited Pto
•Healthcare
•Commuter
•Gym
•Parental Leave
필수 스킬
Python
React
About Mistral
At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.
We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.
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 France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.
Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.
About The Job:
The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.
Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution.
One of our most important customer isn't external: It's us. We're looking for an engineer to build AI-powered internal tools at Mistral. Your job is to make the company run better by deploying our own models across every team. Think of it as being customer zero. You'll identify automation opportunities, build the solutions, ship them to internal users, and learn from real-world usage. Legal document review, HR onboarding workflows, code review assistants, knowledge search, and support triage are all examples of tasks that save time and improve decision-making.
This role matters for two reasons:
- First, a company that builds AI should be the best at using it our internal operations should be a showcase, not an embarrassment.
- Second, every internal deployment is a stress test. You'll find edge cases, discover limitations, and feed those insights directly to product and research. You make our models better by using them.
What you will do
- Identify high-value internal use cases across engineering, legal, HR, sales, and operations
- Build or vibe code end-to-end LLM applications: prompts, RAG pipelines, APIs, simple UIs, deployment, and monitoring
- Own the full lifecycle: prototype → production → maintenance → iteration
- Document learnings and share insights with product and research teams
- Convert successful internal tools into customer demos or case studies where appropriate
How We Work in Applied AI:
- We care about people and outputs.
- What matters is what you ship, not the time you spend on it
- Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
- Always ask why. The best solutions come from deep understanding, not from copying what worked before
- We say what we mean. Feedback is direct, timely, and given because we care.
- No politics. Low ego, high standards.
- We embrace an unstructured environment and find joy in it.
About you
- You are fluent in English
- You have 3+ years building production software, with meaningful experience deploying LLM applications
- You’ have a bias toward shipping, you'd rather have a working prototype than a perfect specification
- You have strong technical coding skills in Python and front-end Skills with React Frameworks
- You’re comfortable working autonomously across teams with different needs and constraints
- You have strong communication skills; you'll be the bridge between non-technical teams and AI capabilities
Ideally you have:
- Contributions to open-source evaluation frameworks (e.g., LM Eval Harness, OpenAI Evals) or published research on LLM evaluation
- Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect or Technical Product Manager
- Experience with ML frameworks (Py Torch, Hugging Face Transformers)
Benefits:
🏝️ PTO: The CDI contract will be a "Forfait 218 jours", corresponding to 25 days of holidays and on average 8 to 10 days of RTT days, and complete autonomy on working hours
⚕️ Health : Full health insurance coverage for you and your family
🚗 Transportation : We offer a €600 annual mobility allowance. This package covers 50% of your public transportation costs and includes the Sustainable Mobility Allowance (FMD), encouraging eco-friendly travel options such as cycling or carpooling.
🥕 Food : Swile meal vouchers with 10,83€ per worked day, incl 60% offered by company
🏀 Sport : Gymlib - sponsorship by Mistral of a significant part of the monthly fee (depending on the program you chose)
🐤 Parental policy : 4 additional weeks for parents on top of what is offered by the French state.
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Mistral AI 소개

Mistral AI
Series BMistral AI is a French artificial intelligence company that develops and provides large language models and AI solutions. The company focuses on creating efficient and powerful AI models for various applications.
51-200
직원 수
Paris
본사 위치
$6.0B
기업 가치
리뷰
3.8
10개 리뷰
워라밸
2.5
보상
4.0
문화
4.2
커리어
3.5
경영진
2.3
72%
친구에게 추천
장점
Supportive team environment
Good compensation and benefits
Innovative projects and cutting-edge technology
단점
Poor management and lack of direction
Work-life balance issues and heavy workload
Fast-paced stressful environment
연봉 정보
37개 데이터
Mid/L4
Senior/L5
Staff/L6
Mid/L4 · Applied AI Engineer
2개 리포트
$214,500
총 연봉
기본급
$165,000
주식
-
보너스
-
$195,000
$234,000
면접 경험
1개 면접
난이도
3.0
/ 5
소요 기간
21-35주
면접 과정
1
Application Review
2
Recruiter Screen
3
Technical Interview
4
Research Presentation
5
Team Matching
6
Offer
자주 나오는 질문
Machine Learning/AI Algorithms
Research Experience
Technical Knowledge
Coding/Implementation
Behavioral/STAR
뉴스 & 버즈
Generative AI Platforms - Trend Hunter
Trend Hunter
News
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5d ago
How France’s Mistral Built A $14 Billion AI Empire By Not Being American - Forbes
Forbes
News
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5d ago
Connect the dots: Build with built-in and custom MCPs in Studio - Mistral AI
Mistral AI
News
·
6d ago
The OpenAI / TBPN Audit: Why Anthropic’s Next Acquisition Should Be a Regulatory Network
https://preview.redd.it/q7ltkacfu2tg1.jpg?width=3000&format=pjpg&auto=webp&s=261ce6e7090baf84297a882ffa5b7e62f0d09955 # Forensic Audit: OpenAI’s TBPN Acquisition, the Enterprise Trust Gap, and the Dawn of Regulatory Media **Listen to audio at** [**https://enoumen.substack.com/p/the-openai-tbpn-audit-why-anthropics**](https://enoumen.substack.com/p/the-openai-tbpn-audit-why-anthropics) OpenAI just spent hundreds of millions to buy the Silicon Valley narrative. It’s a brilliant cons
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