AI Engineer

AI Engineer

As our AI Engineer, you will be at the forefront of AI innovation, working on groundbreaking technology that combines large language models with formal verification methods. You will design and develop the next generation of formally verified AI systems, focusing on novel architectures, orchestration protocols, and training methodologies that eliminate hallucinations while dramatically reducing computational costs. Your work will transition from research breakthroughs to real‑world deployment with design partners in high‑stakes domains such as healthcare and enterprise software.

Location: Paris, France

Key Responsibilities

• Design and develop AI systems: Lead the architecture and implementation of LLMs integrated with formal verification methods.
• Build orchestration protocols: Design and implement orchestration frameworks, including tool calling, structured generation, and verification workflows.
• Drive research innovation: Actively shape the company's research roadmap, exploring new architectures, training methodologies, and verification techniques in collaboration with our scientific advisory board.
• Deploy with design partners: Work closely with 2‑3 early customers in high‑stakes domains to implement proof‑of‑concept solutions that demonstrate measurable improvements in AI reliability and cost‑efficiency.
• Optimize training and evaluation: Develop advanced dataset generation pipelines, fine‑tuning workflows (DPO, RLHF), and rigorous evaluation protocols to continuously improve model performance.
• Build reusable infrastructure: Create documentation, code templates, and engineering best practices that enable the team to scale our deployment approach as we grow.
• Bridge theory and practice: Translate cutting‑edge research in AI into production‑grade systems.

Essential Qualities

• Research‑driven curiosity: Passionate about exploring novel AI applications and architectures, pushing the boundaries of what’s possible.
• Hands‑on technical excellence: Design, implement, and deploy production‑grade AI systems autonomously, from model training to orchestration.
• Deep technical expertise: Extensive knowledge of LLM architectures, training methodologies, and inference optimization.
• Bridge builder: Translate complex research concepts into practical implementations.

Background

• 3+ years of hands‑on experience building and deploying AI/ML systems, with deep expertise in Python, LLM APIs, and cloud infrastructure.
• Strong foundation in machine learning fundamentals, model architectures, and modern AI engineering practices.
• Deep knowledge of the latest developments in AI research and production systems.

Required Skills

• Python mastery: Write clean, efficient Python code and understand object‑oriented programming principles deeply.
• Fullstack fundamentals: Understand both frontend and backend development principles, work across the stack when needed, and proficient in Python for backend systems.
• LLM expertise: Hands‑on experience with large language models, including API integration, prompt engineering, and orchestration frameworks.
• LLM inference packages: Practical experience with at least one major LLM inference framework (vLLM, llama.cpp, TensorRT‑LLM, or similar) and understanding of inference optimization techniques.
• Training & fine‑tuning: Implement fine‑tuning workflows (DPO, RLHF, or similar) and understand dataset generation and model evaluation.
• Model architectures: Deep knowledge of transformer architectures and modern inference optimization techniques.
• Production experience: Deployed AI systems in production environments and understand the full ML lifecycle from training to deployment.
• Research mindset: Stay current with the latest AI research and quickly prototype and validate new ideas.

Benefits

• Competitive cash salary and equity (BSPCE) in a high‑potential company.
• Health insurance (Alan) for you, partner, and children.
• Daily lunch vouchers (Swile).
• Hybrid work model with a strong emphasis on in‑office collaboration (typically 3‑4 days per week).
• 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.
• World‑class team: Collaborate with a scientific advisory board from leading institutions and experienced business angels from top tech companies.
• 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.