---
title: 'Research Engineer, Forge at Mistral'
canonical: 'https://feeny.ai/job/research-engineer-forge-mistral-paris-asefppy5fxzc'
type: 'job'
last_seen: '2026-09-06'
---

# Research Engineer, Forge at Mistral

- **Company:** [Mistral](https://feeny.ai/companies/mistral)
- **Location:** Paris, France
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-04
- **Last confirmed live:** 2026-09-06
- **Apply:** https://jobs.ashbyhq.com/mistral.ai/1808c0af-7352-4d0b-9e35-d3d6704e4759

## Job description

## 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.

## ROLE SUMMARY

As a Research Engineer on Forge, you will turn real customer requirements into reliable training and deployment workflows. You’ll work end‑to‑end across model adaptation and post‑training (CPT/SFT/RL/distillation), evaluation, data, and infrastructure. The role bridges research experimentation and production constraints.

This role sits in Applied Science, with direct impact on client outcomes. You’ll collaborate closely with scientists, engineers, product, and customer‑facing teams to ensure Forge projects ship, are maintainable, and can be trusted by others.

Interview focus can vary (algorithms, infrastructure, evals, or data). You don’t need to match every bullet below to apply.

## WHAT YOU WILL DO

- Build and improve post‑training and evaluation workflows (CPT/SFT/RL/distillation), turning prototypes into repeatable Forge “recipes”.
- Develop tools and pipelines for synthetic data generation, data curation, training, evaluation, and deployment.
- Debug and harden large‑scale ML systems: distributed training, scheduling/execution, checkpointing, observability, and reproducibility.
- Improve the Forge codebase via clear APIs, tests, documentation, and maintainable abstractions.
- Push the frontier of our RL training stack (e.g., high-throughput async rollout and scalable post‑training systems at frontier-model scale)
- Make sure Forge deployment is seamless and adaptable to a diversity of clients (hardware access, software stack, cloud and on-premises, …)
- Partner with researchers and infrastructure engineers to translate bottlenecks into concrete system improvements.

## ABOUT YOU

- Strong Python engineering skills and experience working in large codebases (testing, code review, CI, operational ownership).
- Hands‑on experience with PyTorch, JAX, or similar.
- Strong systems and infrastructure fundamentals.
- Experience with LLM training or post‑training: fine‑tuning, RL, distillation, evaluation, and/or data pipelines.
- Excellent debugging skills in ambiguous systems (distributed jobs, data issues, quality regressions, infra failures).
- Clear communication with technical and non‑technical stakeholders.
- High agency, low ego, and comfort in fast‑moving, under‑specified environments.

## NICE TO HAVE

- Distributed training experience (FSDP, DeepSpeed, Megatron, etc.).
- Cluster/orchestration experience (SLURM, Ray, Kubernetes, Kueue, Karpenter, Skypilot, etc.).
- Experience building reliable ML infrastructure, evaluation systems, or large‑scale data processing pipelines.
- Research experience in LLMs, agents, multimodal models, reasoning, code, or domain adaptation.
- Open‑source contributions, publications, or widely used internal tooling.
- Experience training multi‑billion‑parameter models (pre‑training or RL). Experience training on petabyte- and exabyte-scale datasets.
- Ability to identify bottlenecks across the stack and drive improvements from first principles.

## 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 https://app.notion.com/p/mistralai/Benefits-at-Mistral-36e6ba59a7fe836b93dd01737fcc27ef?source=copy_link.

## PRIVACY POLICY

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy https://legal.mistral.ai/terms/applicant-privacy-policy.

## About Mistral

## Company Overview
- **One-liner**: Mistral is a French AI company building open, frontier-grade large language models, developer platforms, and applied AI solutions for enterprises and governments.
- **Entity Type**: Private (Series C)
- **Headquarters**: Paris, France (15 rue des Halles)
- **Founded**: April 2023
- **Founders**: Arthur Mensch (CEO), Guillaume Lample (Chief Science Officer), Timothée Lacroix (CTO)

## Core Business
- **Primary industry/industries**: Artificial Intelligence, Large Language Models, Enterprise AI Software
- **Target customers**: B2B, Enterprise, Government, and Developers (B2D)
- **Mission or purpose statement**: "To make frontier AI open to all, and together solve the world's hardest problems."

## Products & Services
- **Mistral Large**: Frontier-grade large language model for complex reasoning and enterprise tasks.
- **Mistral Small 3**: Efficient, lightweight model for cost-sensitive deployments.
- **Mistral Code / Vibe**: AI agent for long-horizon, autonomous software development and task completion.
- **Le Chat**: Consumer-facing AI assistant and chatbot.
- **Mistral OCR 4**: State-of-the-art document intelligence model for extracting and understanding text from images and PDFs.
- **Mistral Forge**: Custom model development service for training, aligning, and evaluating proprietary AI models on private data.
- **Mistral Studio**: Platform for building, testing, and running AI agents and applications with full control.
- **Mistral Compute**: Infrastructure and orchestration platform for frontier-scale training and inference (edge to cloud).
- **Mistral Search Toolkit**: Tools for integrating search and retrieval into AI applications.
- **Voxtral**: Voice AI model for speech-based interactions.

## Market Standing
- **Valuation/Market Cap**: $4.016 billion (latest reported valuation, per CB Insights; date not specified but likely post-Series C)
- **Key Metric**: Total funding raised across Seed, Series A, Series B, and Series C rounds (specific amounts not disclosed in search results).
- **Notable Investors/Partners**: Not explicitly named in search results, but the company partners with organizations in finance, manufacturing, defense, energy, and the public sector.
- **Growth Signals**: 
  - Rapid scaling: 900+ employees across 30+ nationalities as of mid-2026.
  - 50% of leadership roles held by women.
  - Key product launches on a near-monthly cadence (e.g., Mistral OCR, Forge, Vibe, Compute, Search Toolkit, Voxtral).
  - Strong presence in high-stakes, regulated industries (defense, energy, public sector).

## Competitive Advantages
- **Open-source DNA**: Commitment to openness, transparency, and cost efficiency differentiates Mistral from closed, Big Tech AI labs.
- **Full-stack ownership**: Controls the entire stack from frontier models to developer tools, applications, and compute infrastructure, enabling deep customization and reliability.
- **European leadership**: Positioned as a sovereign, European AI champion, appealing to governments and enterprises seeking data control and regulatory compliance.
- **Speed and rigor**: Culture of rapid experimentation, iteration, and data-driven decision-making.

## Strategic Focus
- **Enterprise and government partnerships**: Co-creating tailored AI systems for mission-critical use cases in finance, manufacturing, defense, energy, and public sector.
- **Open platform ecosystem**: Expanding Mistral Studio and Forge to enable customers to build custom models and agents on their own data.
- **Infrastructure as a product**: Commercializing Mistral Compute to become a platform for others to train and run AI workloads.
- **Continuous model innovation**: Releasing new frontier models and capabilities (OCR, voice, code agents) at a rapid pace.

## Why Work Here
- **Culture**: Flat structure, high ownership, low ego, and a "builders, not order takers" mentality. The company values audacity, speed, rigor, and customer centricity.
- **Remote/Hybrid/Office**: Based in Paris (15 rue des Halles); relocation support and visa sponsorship offered. Specific remote/hybrid policy not detailed, but global team suggests flexibility.
- **Notable perks and benefits** (from careers page):
  - 20 weeks paid parental leave for all birthing parents.
  - 100% employer-sponsored medical, dental, and vision coverage for employees and dependents.
  - 6% 401k match (US) / 5% pension contribution (UK).
  - Childcare support (reserved daycare seats or financial assistance).
  - Meal allowances and transportation support.
  - Fitness and wellness subsidies.
  - Relocation and settling-in services.
  - Financial and career planning support.
- **Team composition**: 900+ employees from 30+ nationalities; 50% female leaders.
- **Interview process**: For science, product, and engineering roles: intro conversation → 2-5 technical exercises → 1-3 interviews (hiring manager + teammates) → values conversation → reference checks.

## Sources
1. [Mistral AI - About Page](https://mistral.ai/about/)
2. [Mistral AI - Careers Page](https://mistral.ai/careers/)
3. [Mistral AI - Homepage](https://mistral.ai/)
4. [CB Insights - Mistral AI Company Profile](https://www.cbinsights.com/company/mistral-ai)
5. [Mistral AI - LinkedIn](https://www.linkedin.com/company/mistralai)

## Other roles at Mistral

- [Partnership Development Manager GSI DACH](https://feeny.ai/job/partnership-development-manager-gsi-dach-mistral-munich-tc1nyn35je06) — Munich, Germany
- [Reseach Engineer, Full Stack](https://feeny.ai/job/reseach-engineer-full-stack-mistral-palo-alto-em0x4tqd599e) — Palo Alto, CA
- [AI Scientist - Physics Models](https://feeny.ai/job/ai-scientist-physics-models-mistral-paris-nczvzn6411p2) — Paris, France
- [AI Scientist - Agentic Engineering](https://feeny.ai/job/ai-scientist-agentic-engineering-mistral-paris-vnpqnmhgxgmc) — Paris, France
- [Engineering Team Lead, Mistral Cloud](https://feeny.ai/job/engineering-team-lead-mistral-cloud-mistral-paris-9gb48mbqamc8) — Paris, France
- [Customer Success, North America](https://feeny.ai/job/customer-success-north-america-mistral-new-york-2b2yrzajm1pw) — New York, NY
- [AI Developer Relations Engineer](https://feeny.ai/job/ai-developer-relations-engineer-mistral-san-francisco-e0v3rpkyx40a) — San Francisco, CA
- [Research Engineer, ML Platform](https://feeny.ai/job/research-engineer-ml-platform-mistral-palo-alto-znvgpkdp419r) — Palo Alto, CA
- [Engineering Team Lead, Backend](https://feeny.ai/job/engineering-team-lead-backend-mistral-paris-zycgqy241z1e) — Paris, France
- [Talent Acquisition Specialist , GTM & Corporate - EMEA](https://feeny.ai/job/talent-acquisition-specialist-gtm-corporate-emea-mistral-paris-qv1feqt86jfk) — Paris, France