About this role

Lead technical development, product engineering, and infrastructure for AI for Drug Discovery group
Oversee all facets of AI4DD engineering including deploying production applications and building data engineering pipelines
Partner with research teams to optimize infrastructure for foundation model training and workflow orchestration
Manage project execution, resource allocation, and budget planning
Collaborate with cross-functional teams to translate research prototypes into production-ready systems

At least 5 years of experience in software, data or ML engineering
At least 5 years in a people leadership role managing multi-disciplinary engineering teams
Experience in designing scalable, reliable, and cost-effective data products and computational systems
Hands-on experience building, scaling, and maintaining infrastructure for machine learning/AI workflows (MLOps, distributed training, inference services)
Deep expertise in cloud computing environments (e.g., AWS, GCP, Azure)
Understanding of machine learning algorithms and the lifecycle of developing AI models for complex domains
Preferred experience in the biotech or pharmaceutical industry with exposure to drug discovery or clinical trial data
Master's degree in Computer Science, Engineering, or a related quantitative field.

Relocation benefits are available for this opportunity
Discretionary annual bonus may be available based on individual and Company performance
Health benefits
Employee development programs

ML Engineering Director, AI for Drug Discovery

Key skills