In this role, you will help translate advanced AI modeling into dependable systems that support drug discovery at Eli Lilly, working within a Lilly–NVIDIA AI co-innovation lab environment.
Role Overview
As an AI Engineer, you will build, train, evaluate, and deploy AI systems in collaboration with AI scientists and other engineering teams. The work supports drug discovery by converting sophisticated AI models into tools that can be used in research workflows, within the Lilly–NVIDIA AI co-innovation lab in Silicon Valley.
Key Responsibilities
- Develop and apply innovative AI techniques to address complex business challenges, including tailored solutions that support clinical research processes.
- Build and implement AI-driven models and applications across the full stack, including backend services and frontend interfaces.
- Design and maintain resilient system architectures that support performance, scalability, and security across platforms.
- Support large-scale model development.
- Collaborate with colleagues to gather ideas and insights, contributing to a team culture focused on innovation in AI development.
- Follow ethical guidelines for AI usage and data handling to ensure compliance with regulations and maintain data privacy and security.
- Advance engineering excellence through architecture reviews, code quality leadership, and mentorship, while protecting Lilly proprietary data, models, and intellectual property.
Required Qualifications
- Advanced Python with production experience in PyTorch or JAX, including experience moving machine learning models from research code to working systems.
- Hands-on distributed training experience on multi-GPU, multi-node infrastructure using DDP, FSDP, DeepSpeed, or Megatron, plus GPU performance profiling and optimization.
- Experience optimizing and serving models for inference using Triton, vLLM, or TensorRT-LLM, with containerization and scheduling tools such as Docker, Kubernetes, Ray, or Slurm.
- Experience building model evaluation and benchmarking, including test design that identifies failure modes.
- Full stack capability, including a backend language, front-end familiarity such as JavaScript with a framework like React, and API design for scientist-facing interfaces.
- Comfort with the scientific Python stack including NumPy, SciPy, and Pandas, with C++ or CUDA as a strong plus for performance-critical work.
- Experience with cloud AI/ML platforms such as AWS, Azure, or GCP, alongside on-premises GPU clusters.
- Strong problem-solving skills and the ability to operate effectively in ambiguity in a technical environment.
- Strong written and verbal communication and demonstrated ability to collaborate with research scientists.
- Experience with distributed training or large-scale model deployment on GPU infrastructure.
- Experience working across the full stack of an AI application, including data, model, service, and interface.
Technologies
- Python, PyTorch, JAX
- DDP, FSDP, DeepSpeed, Megatron
- Triton, vLLM, TensorRT-LLM
- Docker, Kubernetes, Ray, Slurm
- JavaScript, React
- NumPy, SciPy, Pandas
- C++, CUDA
- AWS, Azure, GCP
Education
Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related field.
Location and Work Flexibility
This role is based at the Silicon Valley Hub and offers a flexible hybrid model: three days onsite and two days remote each week.
About the Lilly and NVIDIA Partnership
Lilly and NVIDIA are launching a new AI co-innovation lab in Silicon Valley with up to a $1 billion, multi-year commitment to tackle drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists, and biologists together with NVIDIA engineers under one roof. The teams are building purpose-built foundation and frontier AI models trained on Lilly data at scale to tighten the feedback loop between automated wet labs and computational dry labs, with the goal of designing the next generation of medicines for patients globally.
Compensation
The anticipated wage for this position is $141,000 - $253,000. Actual compensation will depend on a candidate’s education, experience, skills, and geographic location.
Benefits
- Company bonus (depending, in part, on company and individual performance)
- Eligibility to participate in a company-sponsored 401(k)
- Pension
- Vacation benefits
- Eligibility for medical, dental, vision, and prescription drug benefits
- Flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
- Life insurance and death benefits
- Certain time off and leave of absence benefits
- Well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)
Accessibility and Employee Resource Groups
Lilly is dedicated to helping individuals with disabilities actively engage in the workforce. If you require accommodation to submit a resume for a position at Lilly, complete the accommodation request form at https://careers.lilly.com/us/en/workplace-accommodation for further assistance.
Employee Resource Groups (ERGs) include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN), and Women’s Initiative for Leading at Lilly (WILL).
