Founder in Residence, Open Application for Founders
The role involves joining Mistral's Solutions team with the mission to take the company's AI models and make them indispensable for enterprise clients. Responsibilities include owning a portfolio of enterprise clients and acting as their primary point of contact and co-builder, identifying high-impact use cases, structuring deployments, and removing obstacles. The role requires bridging the gap between the AI models' capabilities and client needs, addressing issues ranging from prompting to executive-level challenges. Additionally, the person feeds back signals from the field to product and research teams. Depending on background, one may focus either on deployment strategy (including business cases, C-level adoption, executive workshops, adoption roadmaps, and ROI proposals) or on applied AI engineering (including integration architecture, fine-tuning, production deployment, prototypes, deployment pipelines, client code, and open-source contributions).
Statistics & Python Expert - Freelance AI Trainer
Contributors design original computational statistics problems simulating real mathematical research workflows, create problems requiring Python programming to solve using libraries like Numpy, SciPy, and Sympy, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains in number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications, verify solutions using Python with standard mathematical libraries, and document problem statements clearly alongside providing verified correct answers.
Senior Product Manager, Enterprise AI Platform
Define the vision and roadmap for the Enterprise AI platform. Understand key enterprise use cases and pain points through deep engagement with forward deployed teams, turning common pain points into high leverage features. Partner with research, engineering, and design teams to translate AI capabilities into useful product features. Own product lifecycle from ideation through launch.
VP Engineering - Paris
The VP Engineering is responsible for defining and executing a scalable, defensible technology strategy, including architecting and scaling the AI platform with a focus on agents, orchestration, model integration, and infrastructure. They make critical build versus buy decisions across the technology stack, ensure performance, reliability, and cost efficiency at scale, and establish durable technical moats in a rapidly evolving AI landscape. They translate cutting-edge AI capabilities into repeatable, enterprise-ready products, standardize systems that are currently bespoke or forward-deployed, and balance speed of iteration with platform robustness and maintainability. They build and lead a high-caliber engineering organization, scaling from a startup structure to multi-layered, high-output teams and implement processes to enable speed without sacrificing quality. The VP Engineering acts as a key counterpart to the CEO in board and investor discussions, clearly articulates the company's technology and product roadmap, and provides credibility and depth in technical due diligence and fundraising contexts. They operate at the intersection of Research, Product, and Go-to-Market, align engineering execution with customer outcomes and revenue growth, and help define the company’s long-term product and platform positioning.
Parcel Contract Intelligence Consultant
Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.
Applied AI, Forward Deployed Machine Learning Engineer, Critical and Sovereign Institutions, EMEA
The Applied AI Engineer is responsible for the technical design, implementation, and deployment of AI solutions tailored to the needs of critical infrastructure and sovereign institutions. Responsibilities include individually deploying AI solutions into production for use cases with significant operational and strategic impact, developing state-of-the-art GenAI applications specific to sovereign institutions and critical infrastructure, collaborating closely with researchers, AI engineers, and product teams on complex projects involving advanced fine-tuning, LLM applications, and contributions to open-source codebases. The role also involves participating in pre-sales discussions to understand client needs and provide technical guidance on Mistral's products, and working with product and science teams to improve offerings with a focus on security, compliance, and performance.
Manager, Forward Deployed Engineering - Paris
Lead and grow a team of Forward Deployed Engineers (FDE) delivering production systems with frontier models, owning end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality. Codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and the wider developer community. Monitor early indicators in product behavior, customer environments, or delivery practices and raise them with urgency. Use judgment to determine what requires action and set high performance standards for the FDE team while supporting individual growth through direct and actionable feedback. Define staffing and support strategies for scalable field teams without added complexity.
Graduation Internship - AI Research - Paris
Participate in research and development within the Models team, Data Research team, or Agent team in H Company's research lab as a graduation internship; work on building foundational models powering agentic technology, advancing multimodal intelligence through large-scale models, and defining new learning algorithms and agent paradigms for autonomous AI systems.
Mathematics & Python Expert - Freelance AI Trainer
Contributors may design original computational mathematics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks), develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly while providing verified correct answers.
AI Product Manager, Paris
Define and drive the AI product roadmap, ensuring alignment with business objectives and user needs. Collaborate with cross-functional teams, including engineering, design, and marketing, to develop and launch AI-powered features. Conduct market research and analyze user feedback to identify opportunities for AI integration. Work closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact. Define key performance indicators (KPIs) to measure success and iterate based on data-driven insights. Stay up to date with AI trends, emerging technologies, and best practices to ensure products remain competitive. Ensure ethical AI usage and compliance with data privacy regulations.
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