Director, Generative Molecular Design & Optimization

100 Eli Lilly and Company; San Diego (CA); On-site; USD 194,000 - 339,000; Full time

Benefits offered by this job

401(k)

Pension

Vacation benefits

Medical benefits

Job summary

Eli Lilly and Company in San Diego leads pioneering generative design and optimization for biotherapeutics. The role guides conditioning, sampling, scoring, and integration of design workflows across therapeutic discovery programs.

The position requires a PhD with a strong track record in computational molecular design, deep learning, and leadership of cross-disciplinary teams, with collaboration across model and validation groups.

Qualifications

• Ph.D. in a STEM field with 3+ years experience; or an M.S. with 6+ years; or a B.S. with 8+ years.
• Track record leading computational or generative molecular design efforts that resulted in experimentally evaluated designs.
• Expertise in designing and building training/evaluation datasets for sequence, structure, or molecular design models.
• Strong Python skills and experience with a modern deep learning framework and GPU computing.

Responsibilities

• Conditioning and controllable molecule design to steer designs toward epitope-specific antibodies.
• Sampling and optimization to maximize design quality and discovery efficiency.
• Scoring and ranking that combine learned and physics-based signals for design prioritization.
• Training corpus strategy with provenance, splits, and leakage controls.
• Build and scale integrated design pipelines across generation, sampling, optimization, scoring, and selection.

Skills

Generative design

Deep learning

Python

GPU computing

Leadership

Education

PhD in computer science or related STEM

MS with 6+ years of experience

BS with 8+ years of experience

Job description

Eli Lilly and Company in San Diego leads pioneering generative design and optimization for biotherapeutics. The role guides conditioning, sampling, scoring, and integration of design workflows across therapeutic discovery programs.

The position requires a PhD with a strong track record in computational molecular design, deep learning, and leadership of cross-disciplinary teams, with collaboration across model and validation groups.