Advisor, AI/ML Gen Design for Biotherapeutics

BioSpace; San Diego (CA); On-site; USD 168,000 - 268,000; Full time

Job summary

Lilly Biotechnology Center in San Diego is expanding a generative design platform for biotherapeutics. You will develop and train protein/antibody foundation models at scale, integrate AI with experimental validation, and advance state-of-the-art methods in a multidisciplinary team. The role involves hands-on research, collaboration with wet-lab scientists, and publishing results at conferences.

A Ph.D. or MS with relevant ML/biology experience is required, with strong Python/PyTorch skills and

Qualifications

• Ph.D. in a quantitative field or MS with 3+ years in ML/computational biology
• Fluency in Python and PyTorch with hands-on experience training DL models on GPUs, including multi-node or distributed runs

Responsibilities

• Develop model architectures for protein design across sequence-structure generation, epitope conditioning, and confidence prediction
• Invent and implement novel AI methods for foundation models and generative AI in biotherapeutics
• Run training at scale, manage LillyPod GPUs, and document configurations and results for reproducibility
• Curate and preprocess training data (structure, sequence, assay data) with subject matter experts
• Evaluate model outputs against experimental results to calibrate and improve performance
• Diagnose failures, identify root causes, and improve architectures or data strategies
• Collaborate with protein scientists and automation teams to benchmark performance
• Communicate results clearly to computational and wet-lab audiences and publish findings

Skills

Python

PyTorch

Distributed training

Education

Ph.D. in computer science or related quantitative field

MS with 3+ years of relevant research experience

Tools

GPUs

Distributed computing frameworks

Job description

Lilly Biotechnology Center in San Diego is expanding a generative design platform for biotherapeutics. You will develop and train protein/antibody foundation models at scale, integrate AI with experimental validation, and advance state-of-the-art methods in a multidisciplinary team. The role involves hands-on research, collaboration with wet-lab scientists, and publishing results at conferences.

A Ph.D. or MS with relevant ML/biology experience is required, with strong Python/PyTorch skills and