AI Engineer

In this AI Engineer role at Eli Lilly, you will translate advanced machine learning models into dependable capabilities that support drug discovery. Working in a Lilly–NVIDIA AI co-innovation lab setting, you will collaborate with AI scientists and engineering teams to build, evaluate, and deploy AI systems.

Role Focus

Develop and apply innovative AI methods to address complex business challenges, with an emphasis on solutions that support AI scientists and improve clinical research workflows. Build end-to-end AI systems that can be deployed as full-stack applications, from backend services to interfaces used by internal teams.

Responsibilities

• Develop and apply innovative AI techniques to solve complex business problems, delivering tailored solutions that create strategic value and transform 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 to support strong performance, scalability, and security across platforms.
• Lead and support large scale model development.
• Collaborate effectively with colleagues to share ideas and insights, strengthening team innovation and creative problem-solving.
• Follow ethical guidelines for AI usage and data handling, ensuring compliance with applicable regulations and maintaining data privacy and security standards.
• Advance engineering excellence through architecture reviews, code quality leadership, and mentorship, while protecting Lilly proprietary data, models, and intellectual property.

Required Qualifications

• Python experience with production development, including PyTorch or JAX, plus a record of moving machine learning work from research code to working systems.
• Hands-on experience with distributed training on multi-GPU and multi-node infrastructure (e.g., DDP, FSDP, DeepSpeed, Megatron), including GPU performance profiling and optimization.
• Experience optimizing and serving models for inference using tools such as Triton, vLLM, or TensorRT-LLM, along with containerization and scheduling (e.g., Docker, Kubernetes, Ray, Slurm).
• Experience building evaluation and benchmarking for models, including test design that identifies failure cases as well as successes.
• Full stack capability spanning backend language, frontend familiarity with JavaScript and frameworks such as React, and API design to support scientist-facing interfaces.
• Comfort with the scientific Python stack, including NumPy, SciPy, and Pandas. C++ or CUDA experience is a strong plus.
• Experience with cloud AI/ML platforms such as AWS, Azure, or GCP, and working with on-premises GPU clusters.
• Strong problem-solving skills and the ability to work through ambiguity in a highly technical environment.
• Strong written and verbal communication skills and demonstrated ability to partner 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 layers.

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 and Experience

• Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, Engineering, or a related field.
• Minimum 4 years of hands-on engineering experience building machine learning systems, including taking models from research or prototype into real working use.

Location and Work Model

This role is based at Eli Lilly’s Silicon Valley Hub, offering a flexible hybrid work model: three days onsite and two days remotely each week.

Compensation

The anticipated wage for this position is $141,000 - $253,000 per year. Actual compensation will depend on 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)

Lilly and NVIDIA AI Co-Innovation Lab

Lilly and NVIDIA are launching a new AI co-innovation lab in the heart of Silicon Valley, with an up-to-$1 billion, multi-year commitment to solve drug discovery’s toughest challenges. The lab brings Lilly scientists, technologists, chemists, and biologists together with NVIDIA engineers under one roof to build purpose-built foundation and frontier AI models trained on Lilly data at scale.

Additional Information

• Accessibility: If you require accommodation to submit a resume, complete the workplace accommodation request form at https://careers.lilly.com/us/en/workplace-accommodation.
• Employee Resource Groups (ERGs): Africa, AMECA, BE@Lilly, CCN, EnAble, Evolve, LIN, OLA, Pride (LGBTQ+ Allies), VLN, and WILL.