[Hiring] Senior AI Scientist/Lead AI Scientist @Owkin

Role Description

We are looking for a visionary ML/AI Scientist to lead the development of our AI Scientist—an autonomous agentic system designed to navigate the complexities of drug discovery. This role isn't just about training models; it's about building "scientists in a box" that can reason over biological data, design experiments, and autonomously drive therapeutic breakthroughs. Unlike traditional ML roles that focus on single-task optimization, you will be building a meta-researcher. You’ll be at the heart of Owkin’s mission, creating the engine that will discover the next generation of life-saving therapeutics.

• Architect Agentic Systems:
  • Design and implement sophisticated AI agents capable of multi-step reasoning, tool-use, and self-correction.
• Bridge AI and Wet-Lab:
  • Develop frameworks where agents can propose hypotheses and design "optimal experiments" to be validated in the lab.
• Scale the "Hacker" Approach:
  • Rapidly prototype and iterate on agentic architectures, moving from paper to production-grade code with speed and precision.
• Scientific Leadership:
  • Maintain a watch on the frontier of GenAI and Agentic workflows, publishing high-impact research at the intersection of AI, Biology and Chemistry.

Qualifications

• Demonstrated Expertise in Agentic AI:
  • Deep understanding of LLM reasoning (Chain-of-Thought, ReAct), long-context management, and tool-augmented generation.
• The Hacker Toolkit:
  • Expert-level Python skills with a focus on "building." You should be comfortable writing clean, modular code that interfaces with complex APIs and databases.
• Publication Record:
  • History of contributions to top-tier ML conferences (NeurIPS, ICML, ICLR).
• Technical Foundation:
  • PhD in Computer Science, Machine Learning, or Applied Mathematics (or equivalent high-level industry experience).
• Communication:
  • Ability to explain complex agent behaviors to both AI peers and biological experts. Excellent written and oral communication skills. Fluent in English (French is a plus).
• Team first, highly collaborative mindset.

Requirements

• Preferred Qualifications (The "Big Plus"):
  • Computational Biology or Chemistry expertise.
  • Domain Knowledge: Deep understanding of the "central dogma" data stack—from processing raw sequencing (omics) to interpreting the physics and geometry of macromolecular structures.
  • Closed-loop Discovery: Experience in Active Learning, Bayesian Optimization, or Optimal Experimental Design.
  • Systems Engineering: Experience training and deploying large-scale models or managing complex multi-agent orchestrations.
  • Causal Inference: Experience in understanding "response to treatment" or causal discovery in biological systems.
  • Industry Impact: Proven track record of taking a research concept and turning it into a functional tool used by other scientists.

Benefits

• Flexible work organization
• Friendly and informal working environment
• Opportunity to work with an international team with high technical and scientific backgrounds