Formal Methods Research Scientist

About the Role

We are looking for exceptional individuals to build the innovative bridge that will lead to the next breakthrough in the world of AI: the link between AI and formal methods, developing new LLMs that do not hallucinate, are completely transparent, and consume a fraction of the costs of current LLMs.

Key Responsibilities

• Drive research innovation: Actively shape the company's research roadmap, exploring new leads in applied formal verification in collaboration with our scientific advisory board.
• Bridge theory and practice: Translate cutting‑edge research in formal methods into production‑grade systems, explaining complex technical concepts to customers and stakeholders.
• Stay at the forefront of formal methods and intersection with AI: Monitor cutting‑edge research in both formal verification and AI, identifying emerging techniques and tools that could enhance our systems.
• Build strategic academic partnerships: Establish and execute collaborations with leading research laboratories in formal methods, creating mutually beneficial relationships that drive innovation.

Essential Qualities

• Visionary Researcher: Deep passion for formal literature with creative insight to apply complex theoretical concepts to real‑world scenarios.
• Methodical Scientist: Structural discipline and technical mindset required to architect and execute multifaceted research projects.
• Impact‑driven: Excel at bridging the gap between theory and practice, converting abstract research into functional high‑impact implementations.
• Scientific Collaborator: Academic rigor and operational efficiency to foster long‑term lab partnerships and author scholarly articles.

Background

• PhD in formal methods, SMT solver, verification or related topic.
• Expertise with at least one theorem prover.

Required Skills

• Track record in formal software development: Proven experience developing formally verified software or using formal methods in software development.
• Adaptability & collaboration: Drive to stay current with emerging research, learn new methodologies, pivot research directions, structure R&D collaborations, and write scholarly articles.
• Technical communication: Skilled in articulating complex ideas clearly through scientific writing, presentations, and interdisciplinary collaboration.
• Theoretical & practical knowledge of SMT solvers: Deep understanding of theory and hands‑on experience implementing or working with SMT solvers.

Bonus Skills

• Track record in applied formal methods.
• Proficiency in OCaml.
• Theoretical & practical knowledge of LLMs.

Benefits

• Financial & perks:
  • Competitive 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—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 and experienced business angels.
  • 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.