Head of AI

Who you are

• Master’s degree or PhD in ML/AI or a computational scientific field (machine learning, computer science, physics, applied mathematics)
• 5+ years leading scientific or technical teams, including mentoring, hiring, performance management and roadmap ownership
• Deep expertise in machine learning for complex, high‑dimensional data - experience with SOTA architectures and research‑driven model development
• Strong Python and scientific ML ecosystem experience
• Experience building predictive models for scientific or structured domains (drug discovery, biology, physics, materials, climate, etc.)
• Ability to evaluate and improve model performance, efficiency, and robustness in production‑adjacent environments
• Experience in drug discovery, computational chemistry, or molecular modeling - domain knowledge is a plus but not required
• Familiarity with multimodal ML (e.g., combining structural, sequence, and chemical data)
• Experience scaling ML systems across multiple programs or large‑scale scientific pipelines
• Background in platform or infrastructure‑level ML development
• Contributions to research communities (papers, open‑source, benchmarks)

What the job involves

• 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
• Lead AQEMIA’s ML research organisation by managing, mentoring, and growing a ~15 person team of ML scientists and researchers, fostering autonomy, scientific excellence, and high‑performance execution
• Own the predictive ML modeling roadmap by defining priorities, set direction, and align research initiatives with platform evolution and company strategy
• Drive frontier ML innovation, steer exploration of advanced architectures (transformers, GNNs, diffusion models, multimodal systems) and emerging techniques relevant to scientific AI
• Scale high‑throughput ML workflows by overseeing the design of production‑ready pipelines capable of evaluating massive chemical spaces efficiently and reproducibly
• Collaborate across disciplines partnering with chemistry, biology, physics, engineering and leadership teams to integrate ML insights into discovery workflows and strategic decision‑making
• Ensure scientific rigor and model excellence, establish standards for benchmarking, validation, and robustness across all predictive systems
• Translate research into platform impact ensuring modeling breakthroughs directly accelerate AQEMIA’s drug design cycles and unlock new capabilities for the platform