Key Responsibilities Define and execute the strategic roadmap for the company’s AI-driven drug discovery platform, aligning technology investments with therapeutic pipeline objectives. Architect and lead the development of AI world models and multi-agent intelligent systems, building a next-generation AI-driven discovery engine for targeted protein degradation. Design and deploy predictive platforms integrating generative AI, large language models, and multi-agent frameworks to accelerate degrader design, target identification, and candidate optimization. Build and scale AI infrastructure — including model training pipelines, data engineering workflows, and MLOps — ensuring robustness, reproducibility, and scalability. Collaborate with medicinal chemistry, biology, and structural biology teams to translate AI predictions into experimentally validated drug candidates. Stay at the forefront of AI for Science, evaluating and integrating emerging technologies (foundation models, graph neural networks, diffusion models, reinforcement learning) to maintain competitive advantage. Recruit, mentor, and lead a world-class AI research and engineering team; foster a culture of innovation, scientific rigor, and cross-functional collaboration.

Qualifications PhD in Computer Science, AI/ML, Computational Biology, or related discipline from a top-tier university; or equivalent industry experience at a leading internet/AI company. 8+ years of experience in AI/ML research and engineering, with a strong track record of building and deploying large-scale AI systems in production. Deep expertise in one or more areas: large language models, world models, multi-agent systems, generative AI, graph neural networks, or reinforcement learning. Proven experience leading AI teams and driving strategic technology roadmaps; prior experience in AI for drug discovery, computational biology, or life sciences is a strong plus. Strong publication record in top-tier AI/ML conferences (NeurIPS, ICML, ICLR, CVPR, etc.) or equivalent industry impact. Excellent communication and leadership skills, with the ability to bridge AI research and drug discovery domains.