Director, Molecular AI & Federated Learning

BioSpace; Indianapolis (IN); On-site; USD 177,000 - 282,000; Full time

Benefits offered by this job

Company bonus

401(k) plan

Vacation benefits

Job summary

Lilly, a leading global biopharma company, invites applications for a Director, Molecular AI & Federated Learning in Indianapolis, with activities across TuneLab. This senior role shapes the technical vision for privacy-preserving federated learning and generative chemistry, uniting medicinal chemistry, ADMET and multi-task modeling to accelerate lead optimization.

The role requires PhD and 5+ years ML leadership in drug discovery, with hands-on experience in federated learning, GNNs, and

Qualifications

• PhD in Computer Science, Computational Chemistry, Cheminformatics, or a related computational field.

Responsibilities

• Set the technical vision for federated learning and molecular AI across TuneLab.
• Mentor data scientists and engineers, guiding experimental design and code reviews.
• Design and implement federated architectures (Transformers, GNNs) for large-scale pre-training.
• Advance semi-supervised/self-supervised methods within federated settings.
• Develop robust aggregation strategies and scalable training/inference pipelines.
• Lead multi-task learning across endpoints to improve predictive performance.
• Collaborate with external partners to ensure synthetic feasibility and IP protection.
• Define benchmarks and publish high-impact research results and open science practices.

Skills

Medicinal chemistry

ADMET prediction

Molecular optimization

Federated learning

Multi-task learning

Graph neural networks

Transformers

Foundation models

Research leadership

PyTorch

Education

PhD in Computer Science or Chemistry or related field

Tools

RDKit

DeepChem

PyTorch

TensorFlow

Keras

Job description

Lilly, a leading global biopharma company, invites applications for a Director, Molecular AI & Federated Learning in Indianapolis, with activities across TuneLab. This senior role shapes the technical vision for privacy-preserving federated learning and generative chemistry, uniting medicinal chemistry, ADMET and multi-task modeling to accelerate lead optimization.

The role requires PhD and 5+ years ML leadership in drug discovery, with hands-on experience in federated learning, GNNs, and