Chief Molecular AI & Federated Learning Architect

Eli Lilly and Company; San Francisco (CA); On-site; USD 177,000 - 282,000; Full time

Benefits offered by this job

Travel opportunities

Comprehensive benefits

Job summary

Lilly TuneLab seeks a Director of Molecular AI & Federated Learning to set the technical vision. Lead privacy-preserving federated learning and generative small-molecule design, guiding scientists and external partners through research strategy and rigorous methods.

You will mentor teams, shape research agendas, and drive scalable ML advances across the TuneLab ecosystem, balancing innovation with practical applicability in drug discovery.

Qualifications

• PhD in Computer Science, Computational Chemistry, Cheminformatics, ML, or related field.
• 5+ years of post-PhD ML experience in drug discovery; 8+ preferred.
• Demonstrated technical leadership without formal people management.
• Experience with generative molecular design and multi-task/representation learning.
• Deep understanding of medicinal chemistry and ADMET optimization.
• Hands-on experience with federated learning and privacy-preserving ML.
• Publications in top venues (NeurIPS, ICML, ICLR).
• Proficiency in cheminformatics tools (RDKit, DeepChem) and modern ML frameworks (PyTorch, TensorFlow).

Responsibilities

• Set the technical direction for federated learning and molecular AI across TuneLab.
• Mentor data scientists and engineers, guide experimental design and code review.
• Architect novel federated foundation models (Transformers, GNNs).
• Advance semi-supervised and self-supervised methods for federated data.
• Develop robust, communication-efficient model aggregation (FedAvg, FedProx, SCAFFOLD).
• Profile and optimize training/inference performance; build simulation environments.
• Design multi-task models across endpoints to improve data efficiency.
• Address data/task heterogeneity with personalized models and meta-learning.
• Coordinate downstream adaptation and rigorous validation with task-specific metrics.

Skills

Federated learning

Molecular AI

Generative models

Graph neural nets

PyTorch

Mentorship

Privacy-preserving ML

Education

PhD in relevant field

Tools

RDKit

DeepChem

TensorFlow

Job description

Lilly TuneLab seeks a Director of Molecular AI & Federated Learning to set the technical vision. Lead privacy-preserving federated learning and generative small-molecule design, guiding scientists and external partners through research strategy and rigorous methods.

You will mentor teams, shape research agendas, and drive scalable ML advances across the TuneLab ecosystem, balancing innovation with practical applicability in drug discovery.