Senior AI Science Lead

Scorpion Therapeutics; California (MO); Hybrid; USD 180,000 - 250,000; Full time

Benefits offered by this job

Hybrid work (3 onsite/2 remote)

Job summary

Lilly is seeking a Senior AI Science Lead to set scientific direction and technical strategy for large-scale AI research programs advancing drug discovery. You will lead a team across computational chemistry, genomics, and related areas to translate research into scalable capabilities.

The role requires a PhD in ML/related fields, 6+ years of leadership in ML research, expertise in foundation models and PyTorch, and a strong publication track record.

Qualifications

• PhD in machine learning, computational chemistry, biology, or related field.
• 6+ years in advanced ML research with leadership experience.
• Expertise in foundation models, self-supervised learning, generative AI.

Responsibilities

• Lead a team of AI scientists and engineers across computational chemistry, genomics, and related areas.
• Shape AI model architectures, training paradigms, and evaluation frameworks.
• Translate research into scalable, impactful capabilities.

Skills

Python

PyTorch

Leadership

Foundation models

Self-supervised learning

Education

PhD in ML, computational chemistry, biology, or related field

Tools

ML frameworks

Job description

Role

Senior AI Science Lead responsible for setting scientific direction and technical strategy for large-scale AI research programs to advance drug discovery at Lilly.

Responsibilities

• lead a team of AI scientists and engineers across computational chemistry, genomics, and related areas;
• shape AI model architectures, training paradigms, and evaluation frameworks;
• translate research into scalable, impactful capabilities;
• collaborate closely with Lilly Research Labs, engineering, and external partners like NVIDIA to accelerate scientific outcomes.

Requirements

• PhD in machine learning, computational chemistry, biology, or related field;
• 6+ years in advanced ML research with leadership experience;
• expertise in foundation models, self-supervised learning, generative AI;
• proficiency in Python and ML frameworks such as PyTorch;
• proven publication record.

Preferred

• experience in high-performance distributed AI systems, experimental biology or chemistry workflows, team mentorship, and responsible AI practices.

High-Value

leadership in large-scale AI research, foundation models, drug discovery, Silicon Valley location, hybrid work (3 onsite/2 remote).

Travel

not specified.