Advisor - Agent Research

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 rebuilding the Design-Make-Test-Analyze (DMTA) cycle, infusing scientific automation with foundation models, multi-agent systems, and robotics to make scientific discovery intelligent, autonomous, and fast.

We're seeking a scientist-engineer hybrid to deploy AI-driven discovery platforms directly with portfolio research teams. You'll bridge the gap between cutting-edge agentic AI systems and real-world drug discovery workflows.

• Partner with chemists and biologists to translate scientific workflows into agentic systems
• Deploy and integrate Agentic AI system into active research programs
• Design and implement cloud-native data pipelines connecting lab instruments, databases, and AI models
• Support model deployment, inference services, and experiment tracking (e.g., MLflow)
• Integrate LLM reasoning with domain tools (RDKit, molecular graph ML, ELN/LIMS APIs, instrument drivers) to build composite agents that plan, simulate, and execute DMTA tasks
• Prototype and iterate rapidly on agent planning strategies, memory systems, and human-in-the-loop patterns

• Represent Frontier AI in the broader AI@Lilly and external AI research community: publish, give talks, review papers, and scout emerging trends.
• Evaluate external vendors, open-source projects, and academic collaborations for strategic fit.

• Measurable reduction in DMTA turnaround through autonomous planning and execution
• Seamless transition from prototype to production-deployed AI systems

• PhD (or MS + 2 yrs / BS + 4 yrs equivalent experience) in Bioinformatics, Cheminformatics, Computer Science, or related discipline with demonstrated wet-lab collaboration or experience.
• Approximately 1-2 years of demonstrated experience of applying AI/ML in scientific discipline such as biology, chemistry, neuroscience, or a related field (industry postdoc counts)

• Proficiency in Python and deep experience with ML/Deep Learning frameworks (e.g., PyTorch, Tensorflow, JAX, Hugging Face).
• Hands‑on experience building agentic AI systems (e.g., Lang Chain, OpenAI Agents SDK)
• Experience designing and shipping end-to-end systems in cloud environments (backend APIs, lightweight frontends, and agentic platforms)- Git Hub portfolio a plus
• Strong Dev Ops/engineering skills: version control (git), containerization (docker, kubernetes), Git Ops + CI/CD practices, data systems (Redis, SQL/No
  
  SQL), unit testing, frontend (streamlit, flask)
• Working knowledge of cloud-native (AWS/Azure) pipeline architectures including Nextflow, Argo on Kubernetes
• Familiarity with MLOps, including model versioning, data versioning, and continuous integration/continuous deployment for ML systems.
• Experience with LLM post-training, fine-tuning, or RLHF
• Demonstrable research experience, evidenced by contributions to projects, and ideally through publications in relevant ML/NLP venues (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP).
• Experience mentoring and guiding junior researchers or engineers.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form  for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion,…