AI PhD ML Engineering Intern

100 Eli Lilly and Company; Indianapolis (IN); On-site; USD 120,000 - 136,000; Full time

Benefits offered by this job

Free parking

Lilly LIFE fitness center

Bike garage

Subsidized housing

Job summary

Lilly is seeking a PhD candidate to join the ML Engineering team as an intern, supporting Lilly’s Research AIOS. You will work on sizing parallel replicas, data partitioning, and resumable execution tooling for a heterogeneous GPU/CPU compute fleet, under mentorship.

This 12-week, full-time internship emphasizes hands-on development in AI/ML systems engineering and parallel computing. You’ll gain experience with GPU computing, distributed scheduling, and production-grade code delivery while

Qualifications

• PhD in Computer Science, Applied Mathematics, Physics, Engineering, or related field with at least 2 years of graduate research completed.
• Coursework or research in HPC, distributed systems, or ML systems engineering.
• Experience with containerization (Docker).
• Exposure to batch/distributed job execution in HPC schedulers or Kubernetes.

Responsibilities

• Contribute to the design, implementation, and testing of platform capabilities within the Compute domain.
• Build and ship features for a compute platform’s job-sizing, data-partitioning, and resumable-execution tooling under guidance from a mentor.
• Write well-tested, production-quality code following team standards and participate in code reviews and design discussions.

Skills

Python

Parallel computing

Distributed computing

Git/version control

Education

PhD in Computer Science or related field

Tools

Docker

Job description

Organization Overview

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life‑changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, self‑less work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Functional Overview

Tech@Lilly builds and maintains capabilities using cutting edge technologies like most prominent tech companies. What differentiates Tech@Lilly is that we redefine what's possible through tech to advance our purpose — creating medicines that make life better for people around the world, like data driven drug discovery and connected clinical trials. We hire the best technology professionals from a variety of backgrounds, so they can bring an assortment of knowledge, skills, and diverse thinking to deliver innovative solutions in every area of our business.

The Advanced Intelligence organization sits at the forefront of Lilly's AI transformation, driving artificial intelligence and machine learning to revolutionize how we discover, develop, and deliver medicines to patients. Leading initiatives from AI‑enabled laboratories to Kernel Lilly—the AI‑enabled research infrastructure stack serving as the operating system for pharmaceutical research—to strategic partnerships with world‑class technology companies, to proprietary foundation models trained on Lilly's research data, this team is building the technical foundation for AI‑powered R&D. With deep expertise in cutting‑edge AI technologies and pharmaceutical science, Advanced Intelligence is transforming Lilly into an AI‑first drug discovery organization, accelerating breakthrough treatments to patients.

You will work as a member of the ML Engineering team supporting Lilly’s Research AIOS, reporting to an Engineering Director. You’ll contribute to the Compute domain of the AI Operating System — specifically to the tooling that decides, at job‑submission time, how a model gets scaled out and run reliably across a large, heterogeneous, non‑autoscaling GPU/CPU fleet. You'll build automation that improves the efficiency and resiliency of prototyped models — graph‑based, diffusion, flow‑matching, and language models among them — as they move toward broader production use.

The core of your work will focus on one connected problem with three parts: automatically sizing how many parallel replicas and which hardware to use, partitioning a dataset across those replicas without manual sharding, and making batch jobs resumable so an interruption only re‑does the remaining work instead of starting over.

Basic Qualifications

• Currently pursuing a PhD in Computer Science, Applied Mathematics, Physics, Engineering, or a related field, with at least 2 years of graduate research completed
• Coursework or research experience in at least one of: high‑performance/parallel computing, distributed systems, or ML systems engineering
• Experience with containerization (Docker)
• Exposure to batch/distributed job execution in at least one of: traditional HPC job schedulers (e.g., Slurm, Grid Engine) or running batch workloads in a Kubernetes environment
• Available for 12 weeks full‑time engagement between May–September 2027

Additional Preferences

• Prior experience using AI tools (e.g., generative AI platforms, automation tools, or AI‑assisted research/analytics tools) in an academic, project, or work setting

How You’ll Succeed

• Contribute to the design, implementation, and testing of platform capabilities within the Compute domain
• You will build and ship features for a compute platform’s job-sizing, data-partitioning, and resumable‑execution tooling under guidance from your mentor
• You will write well‑tested, production‑quality code following team architectural standards and design patterns
• You will participate in code reviews, design discussions, and sprint ceremonies

Learning & Growth

• Develop technical depth in ML systems engineering while gaining pharma R&D context. You will gain hands‑on experience with GPU computing, heterogeneous‑cluster scheduling, and distributed/parallel execution of batch workloads
• You will learn how resource‑sizing, data‑partitioning, and fault‑tolerance decisions affect platform performance, cost, and reliability across diverse model architectures
• You will document your work and share learnings with the broader team

Collaboration

• Work effectively within a cross‑functional engineering team. You will pair with senior engineers on complex problems, asking questions and contributing ideas
• You will participate in stand‑ups, retrospectives, and planning sessions
• You will present your intern project outcomes to the team and leadership at the end of the rotation

What You Should Bring

• Curiosity about AI/ML systems and how they’re built at scale
• Foundational programming skills in Python, and comfort with parallel or distributed computing concepts (e.g., MPI, multiprocessing, or distributed data/task frameworks)
• Exposure to machine learning concepts and at least one class of generative or predictive model architecture (coursework, personal projects, or research)
• Familiarity with version control (Git) and collaborative development workflows
• Strong communication skills — ability to ask good questions and document what you learn
• Self‑direction balanced with knowing when to ask for help
• Interest in pharmaceutical research or life sciences applications of AI (preferred, not required)

Internship Activities

• Lilly arranges various intern activities including sporting events, dinners, lunch and learns, volunteer activities etc. to provide opportunities for socializing, professional development, and learning more about Lilly.
• Interns will receive 1 week of paid time off during the Lilly summer shut‑down (July5th–July9th)
• 1:1 mentoring from an experienced professional in the function
• Interns will receive a competitive salary and free parking at their work site, as well as access to Lilly’s LIFE fitness center, bike garage, and many other discounts
• If the intern's job position requires a move from another location, Lilly will provide subsidized housing

Compensation & Benefits

• Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance)
• Interns will receive a competitive salary
• Interns will receive a competitive salary and free parking at their work site, as well as access to Lilly’s LIFE fitness center, bike garage, and many other discounts
• The anticipated wage for this position is $119,850 - $136,000
• In addition, Lilly offers a comprehensive benefit program to eligible employees, including 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; and well‑being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

Equal Opportunity

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Employee Resource Groups

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups 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).

Company Culture

How do we do this? We continue to look for ways to include, innovate, accelerate and deliver while maintaining integrity, excellence and respect for people. We hope that you seek to join us on our journey as we create medicine and deliver improved outcomes for patients across the globe!

#WeAreLilly