Artificial Intelligence/Machine Learning (AI/ML) Engineer

Department

Booth IT: Application Development

About the Department

The University of Chicago Booth School of Business is the second-oldest business school in the U.S. and second to none when it comes to influencing business education and business practices. Since 1898, the school has produced ideas and leaders that shape the world of business. Their rigorous, discipline-based approach to business education transforms students into confident, effective, respected business leaders prepared to face the toughest challenges.

Chicago Booth has the finest set of facilities of any business school in the world. Each of the four campuses (two in Chicago, one in London, and one in Hong Kong) reflects the architectural traditions of its environs while offering a state-of-the-art learning environment.

Chicago Booth is proud to claim:
-an unmatched faculty.
-degree and open enrollment programs offered on three continents.
-a global body of nearly 56,000 accomplished alumni.
-strong and growing corporate relationships that provide a wealth of lifelong career opportunities.

As part of the world-renowned University of Chicago, Chicago Booth shares the University's core values that shape the distinctive intellectual culture. At Booth, they constantly question and test ideas, and seek proof. This extraordinarily effective approach to business leads to new ideas and innovative solutions. Seven of the Booth faculty members have won Nobel Prizes for these ideas - the first business school to achieve this accomplishment.

For more information about the University of Chicago Booth School of Business, please visit: http://www.chicagobooth.edu/.

Job Summary

The University of Chicago Booth School of Business seeks an experienced AI/ML Engineer to drive its AI strategy. This role supports research and academic initiatives by developing and deploying advanced AI solutions. The Engineer will collaborate with faculty and IT teams to design scalable architectures and ensure best practices. Strong software engineering skills, expertise in AI/ML frameworks, and a passion for innovation are essential.

Responsibilities

• Designs, develops, and maintains efficient, scalable, and secure AI/ML applications and APIs to advance academic, research, and business innovation priorities.
• Collaborates with IT infrastructure and development teams to assess AI system requirements, inform hardware/software purchases, and optimize resource allocation both on-premise and in the cloud.
• Defines system requirements and architectural specifications, and integrates advanced AI/ML solutions with Booth’s platforms and enterprise systems to ensure security, reliability, and compliance.
• Provides expert technical support, including debugging, documentation, code review, model evaluation, and pipeline optimization, to faculty, staff, researchers, and students.
• Executes the training, benchmarking, and deployment of Large Language Models (LLMs) using frameworks such as Hugging Face, PyTorch, or TensorFlow, and applies advanced optimization techniques, such as quantization, pruning, KV cache tuning.
• Leads and conducts technical workshops or training sessions for faculty, PhD students, and staff, and develops high-quality documentation and user guides to support AI/ML uptake across Booth.
• Optimizes the performance and scalability of AI/ML workloads through algorithmic and system-level improvements, including evaluation and tuning of CPU vs. GPU usage for cost-effectiveness.
• Monitors and assesses the health and performance of internal and cloud compute platforms, such as Mercury, AWS, and GCP, conducts system diagnostics, and supports continuous platform improvement.
• Builds and maintains strong collaborations with Booth departments, UChicago AI research groups, and external partners, sharing best practices and aligning AI initiatives.
• Translates academic AI research into robust, production-ready solutions that drive Booth’s educational and research objectives, and contributes to technology evaluations, research proposals, and cross-functional teams where AI/ML expertise is required.
• Leads in the development of new systems, features, and tools. Solves complex problems and identifies opportunities for technical improvement and performance optimization. Reviews and tests code to ensure appropriate standards are met.
• Acts as a technical consultant and resource for faculty research, teaching, and/or administrative projects.
• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a college or university degree in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through