Advisor - Lab Automation Software Engineer

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

We are seeking a Lab Automation Software Engineering Advisor to join our biotherapeutics discovery automation team at the Lilly Biotechnology Center in San Diego, where you'll architect and implement revolutionary software solutions that transform how we discover life-saving biotherapeutics.

As a Lab Automation Software Engineering Advisor, you'll be at the forefront of designing and building AI-integrated, closed-loop autonomous discovery ecosystem whereby intelligent systems propose hypotheses, execute experiments through advanced robotics, analyze results instantly, and iteratively refine and design the next set of experiments - all with minimal human intervention. In your role, you'll harness the latest breakthroughs in AI, machine learning, and laboratory digitalization to build software that makes our biotherapeutics discovery automation lab smarter, faster, and more innovative than ever before.

If you're excited about harnessing AI and automation to solve real-world problems in drug discovery and want to be part of building the lab of the future, we want to hear from you.

You will have the opportunity to:

• Design and develop software applications that orchestrate complex automated laboratory workflows and closed-loop learning systems.

• Build data pipelines and visualization tools that provide real-time insights into lab operations and experimental outcomes.

• Implement machine learning models for visual inspection systems, predictive maintenance, and process optimization that enhance operational efficiency.

• Create digital lab infrastructure including IoT integrations, digital lab twin models, and telemetry monitoring systems.

• Develop and maintain integrations across multiple automation schedulers, LIMS, and data platforms.

• Ensure robust software deployment through best DevOps practices and cloud-based solutions.

Basic Qualifications:

• Ph.D. in Computer Science, Software Engineering, Bioengineering/Engineering with at least three years of industry experience.

• M.S. in Computer Science, Software Engineering, Bioengineering/Engineering with at least 10 years of experience.