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Aqemia

Head of AI

Paris

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hirly's read of this role

Seniority
Lead / management
Country
FR
Work mode
On-site / unstated
First seen by hirly
28 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

About AQEMIA

AQEMIA is a drug invention company dedicated to creating entirely new medicines to address major unmet medical needs. At the core of our mission is QEMI , our proprietary molecule-invention platform, which uniquely combines cutting-edge science with advanced technology. Powered by physics-based modeling, statistical mechanics, and generative AI, QEMI allows our teams to design novel drug candidates from first principles.

What makes AQEMIA different is our commitment to true innovation: our research is dedicated to the invention of new molecular entities, not the refinement of existing ones. We focus on inventing never-before-seen molecules , without relying on experimental data, and advancing them into a growing pipeline of proprietary programs and strategic partnerships with leading pharmaceutical companies.

Our most advanced preclinical programs are currently in vivo optimization , targeting diseases still waiting for effective treatments, offering our teams the opportunity to work on science that can make a real difference in people’s lives.

For more information, visit AQEMIA.com, our WTTJ Page , and our LinkedIn .

About our Team

AQEMIA brings together a diverse, multidisciplinary team of 80+ professionals based in Paris and London. Our scientists and engineers, including chemists, physicists, machine learning experts, and software engineers, work side by side to push the boundaries of early-stage drug discovery.

This close collaboration across disciplines is central to our approach, enabling us to tackle complex scientific challenges from first principles and translate cutting-edge ideas into novel therapeutic candidates. At AQEMIA, team members are encouraged to contribute their expertise, learn from one another, and play an active role in shaping the future of drug invention.

About our Platform Department

The Platform team (~20 people) brings together multidisciplinary teams working on the scientific core of Aqemia’s drug discovery engine. Its mission is to build scalable and reproducible workflows enabling multiple drug discovery programs to run in parallel with minimal manual intervention.

The team combines expertise across Artificial Intelligence and Machine Learning (both research and applications), data science, statistical physics and molecular simulations, computational chemistry (CADD), and other scientific disciplines. Together, they develop predictive models, physics-based simulations, and robust scientific pipelines that power AQEMIA's discovery platform.

At the center of this ecosystem is the “Rocket Launcher” process: an industrialized workflow continuously launching, testing, and improving drug discovery projects through iterative scientific feedback loops.

The role

AQEMIA is building one of the most ambitious applications of AI with physics: predictive systems that can evaluate and design drug candidates at massive scale. As Head of AI, you will lead the team responsible for the foundational models and high‑throughput workflows that power our discovery platform. This is a strategic and people‑focused role: you will manage and mentor a 10-15 people ML research team, define the roadmap, set priorities, and ensure execution across research, engineering, and scientific stakeholders.

You’ll operate at the intersection of frontier machine learning, scientific modeling, and platform‑level systems design, guiding the development of architectures capable of understanding complex molecular environments and making high‑impact predictions. Your work blends state-of-the art ML thinking with leadership, decision‑making, and cross‑functional alignment. Within 12 months, success means delivering breakthroughs in predictive accuracy, throughput, and reliability, enabling AQEMIA to accelerate discovery cycles and push the boundaries of scientific AI.

Original posting on Aqemia's site ↗

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