🇫🇷 Gif-sur-Yvette, France · 5h ago
Python Product Engineer
Institut DataIA Paris-Saclay
LinkedInEnglish-friendly
Formel AIAt Formel AI, we combine the creativity of generative AI with the reliability of mathematical formal methods. By leveraging the verification capabilities of formal methods, such as the Lean 4, we pioneer a new generation of Large Language Models (LLMs) that are reliable, transparent, and cost-efficient. We're honored to have received the 2nd spot of the Innovation Prize from École normale supérieure in Nov 2025.Formel AI is founded by Sylvain Combettes (CEO) and Antoine Mazarguil (CTO), who met during their PhDs at ENS Paris-Saclay. We closed an oversubscribed angel round in Feb 2026, backed by 30+ top-tier business angels including the founders of Datadog, Dataiku, Nabla, and Artefact. Our scientific advisory board includes Full Professors from Ecole polytechnique, ENS Paris-Saclay, and Ecole des Ponts.We're now onboarding our first design partners and building the team to make it happen. Come join us!AdresseFormel AI75000 ParisFranceDétail de l'offre (poste, mission, profil)Corps de texteAbout The RoleAs our Python Product Developer, you will be at the forefront of building the next generation of AI systems—combining large language models with formal verification methods to create hallucination-free, transparent, and cost-efficient solutions.This is a hands-on technical role where you'll design and implement core machine learning algorithms, develop product features based on customer feedback, and bridge Python with high-performance compiled languages. You'll work directly with the founding team to shape the product roadmap and translate cutting-edge research into production-ready systems.You'll be joining a founding team of deep-tech experts at a critical inflection point—moving from research breakthroughs to real-world deployment with design partners in high-stakes domains where AI reliability is paramount.Key responsibilitiesDevelop product features: Build and ship production-grade features for our platform, working across the full stack from backend APIs to UI prototypes using PythonCollaborate with design partners: Work closely with 2-3 early customers to gather requirements and feedback, translating their needs into technical specifications and contributing to the product roadmapBuild Python-native bridges: Design and implement high-performance integrations between Python and compiled languages (Rust, Go, C++)Build reusable infrastructure: Create documentation, code templates, and engineering best practices that enable the team to scale our development approach as we growBridge research and practice: Work closely with the founding team, including research scientists, to translate cutting-edge formal methods research into production-ready Python implementationsDesign ML algorithms (long term): Design, prototype, and optimize machine learning algorithms that power our formal verification capabilities, including graph processing, anomaly detection, and optimization techniquesWhat we are looking forEssential qualitiesPython mastery: You speak Python as a second language and literally dream in OOP—you understand object-oriented design patterns deeply and write clean, maintainable codeProduct mindset: You're passionate about building features that match user needs and can respond to customer feedback with elegant technical solutionsPolyglot expertise: You have deep knowledge of bridging Python with high-performance compiled languages and understand the trade-offs involvedA relentless drive for applicability: You prioritize real-world impact, the continuous integration of field feedbackBackground5+ years of hands-on Python development experience with proven ability to build production systemsExperience building machine learning or data-intensive applicationsTrack record of working across multiple programming languages and integrating different technology stacksRequired SkillsPython full-stack mastery: Proficiency in Python-based backend frameworks (FastAPI, Flask, Django, etc.), solid foundations in databases (SQL, NoSQL), and core skills in cloud computing and server management (any Cloud CLI, Bash, Docker, etc.)UI prototyping: Hands-on experience with a framework like Streamlit, Gradio, Dash, or similarJavaScript fundamentals: Fundamental knowledge of JavaScript for frontend integrationPolyglot programming: Expertise in at least one other programming language such as C++, Rust, Go, etcNative bridges: Proven expertise in bridging Python with compiled languages (developing Python bindings, FFI, ctypes, cffi, pybind11, or similar)ML skills (optional): Demonstrated experience or strong interest in graph processing, anomaly detection, optimization algorithms, and complex data visualizationBenefitsFinancial & perksCompetitive cash salary and equity (BSPCE) in a high-potential company.Health insurance (Alan) for you and your family (partner and kids).Daily lunch vouchers (Swile).Hybrid work model with a strong emphasis on in-office collaboration (typically 3-4 days per week at the office) to foster team cohesion, spontaneous discussions, and deep work together.What makes this role unique:Founding team impact: Join as one of the first employees and shape the trajectory of a moonshot deep-tech company.Mission-driven startup: Help solve the key pressing challenges of AI—the most transformative technology of our era—ensuring LLMs are trustworthy, transparent, and cost-effective, with direct benefits for environmental sustainability.Work with cutting-edge technology: Build systems that combine LLMs with formal verification—an emerging field at the forefront of AI safety and reliability where breakthrough developments happen every week.World-class team: Collaborate with a scientific advisory board from leading institutions (Ecole polytechnique, ENS Paris-Saclay, etc) and experienced business angels from top tech companies (Datadog, Dataiku, Nabla, Artefact, and more).Strategic customers: Work with leading companies in healthcare, enterprise software, and other mission-critical domains.Flexibility of an early-stage startup: Autonomy to define how you work and what you prioritize.Hiring processApply and submit your resume using this Google FormScreening call (30 min): A quick chat with the CTO to align on vision and expectations.In-depth technical discussion (home exercise followed by a 60 min discussion): Best way to decide if we are a great fit as potential collaborators.Technical deep-dive (60 min): A focus on your proficiency with the tools you will use.Founder interview (45 min): Final discussion on strategy, culture fit, and your long-term evolution within the company, with the CTO and CEO.Sourced from LinkedIn. 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