Senior AI Research Scientist, Aqemia

• Strong problem-solving skills, autonomy and a collaborative mindset
• PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience
• Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch, JAX, TensorFlow)
• Demonstrated hands-on experience implementing and deploying deep learning models in production or research environments
• Strong scientific rigor, curiosity, and ability to perform bibliographic research and exploratory R&D
• Pragmatic and Impact-Driven – Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability
• Eagerness to Learn – A strong curiosity for scientific advancements and a willingness to continuously expand your expertise
• Love for High Scientific Challenges – Enthusiasm for tackling complex problems at the frontier of AI and drug discovery
• Team-Oriented – A collaborative spirit, thriving in an interdisciplinary environment
• Humility – Open to feedback and different perspectives, always striving for improvement

Desirable

• As a Senior AI Research Scientist, you will join one of Aqemia’s Drug Discovery Platform AI Teams, composed of 5 AI Researchers, and lead efforts to develop cutting-edge AI algorithms to model protein-ligand systems and predict molecular properties
• You will be a hands-on technical expert pushing the boundaries of what AI can do for drug discovery
• Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform
• You will act as a technical mentor, contribute to high-impact R&D projects, and help integrate innovative AI methodologies into real-world drug discovery applications
• Lead the design and the technical implementation of novel ML algorithms with a strong focus on deep learning, generative models, graph neural networks, and physics-informed AI to predict molecular properties and protein-ligand interactions
• Take part in cutting-edge research and bibliographic exploration. You’ll identify relevant recent publications, benchmark promising ideas, and propose model or pipeline improvements
• Act as a mentor to junior team members, offering guidance on system design, model implementation, debugging, and good coding practices
• Collaborate with AI researchers, computational chemists, and drug discovery teams to translate AI models into actionable scientific insights
• Be deeply involved in coding, from prototyping to deploying production-ready models. You should have a strong software engineering mindset and a passion for writing clean, efficient, and scalable code
• Share best practices in deep learning model development, testing, and reproducibility within the team
• Scale AI models for real-world applications, optimizing model efficiency, interpretability, and generalization to unseen chemical spaces
• International Environment : The work language is English

• Screening call with Talent Acquisition (30 min)
• Interview with your future Manager (45 min)
• 1st technical interview: Paper review (1.5 hours)
• 2nd technical interview: Take-home ML case (1.5 hours)
• Interview with VP Platform and co-founders (1 hour each)