Artificial Intelligence/Machine Learning 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 7+ years of work experience in a related job discipline.

Certifications:

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Preferred Qualifications

Education:

• PhD.

Experience:

• Background or professional experience in business, economics, or finance, leveraging ML/AI for domain-specific applications and effective engagement with faculty or research groups.
• Familiarity with prompt engineering, in-context learning, and evaluation metrics specifically for LLMs.
• Understanding of LLM training/inference optimization at system level: KV cache optimization, Quantization.
• Strong portfolio or history of translating academic research and prototypes into robust, production-ready AI/ML solutions deployed in real-world settings.
• Direct experience deploying, evaluating, and optimizing AI/ML workloads on both cloud (AWS, GCP, Azure) and on-prem platforms, including cost-performance trade-off analysis.

Technical Skills or Knowledge:

• At least two years of experience developing applications in Python, R, Matlab, C# and .NET, preferably within enterprise or academic contexts.
• Hands-on experience training, fine-tuning, and deploying Large Language Models (LLMs) and advanced architectures, including leveraging frameworks such as Hugging Face Transformers.
• In-depth expertise with advanced model optimization and acceleration methods such as quantization, pruning, knowledge distillation, and cache tuning; demonstrable results with LLMs or large-scale neural networks.
• Demonstrable familiarity with AI/ML optimization tools, such as MosaicML, DeepSpeed, ONNX, and their integration into production pipelines.

Working Conditions

• This position is currently expected to work a minimum three days per week in the office.

Application Documents

• Resume/CV (required)
• Cover Letter (required)

Job Family

Information Technology

Role Impact

Individual Contributor

Scheduled Weekly Hours

37.5

Drug Test Required

No

Health Screen Required

No

Motor Vehicle Record Inquiry Required

No

Pay Rate Type

Salary

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FLSA Status

Exempt

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Pay Range

$135,000.00 - $175,000.00

The included pay rate or range represents the University’s good faith estimate of the possible compensation offer for this role at the time of posting.

Benefits Eligible

Yes

The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the Benefits Guidebook.

Posting Statement

The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

All offers of employment are contingent upon a background check that includes a review of conviction history.A conviction does not automatically preclude University employment.Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: http://securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.