Junior Software Developer

Department

About the Department

Job Summary

Responsibilities

• Under the direction of the Principal Investigator, coordinate the day-to-day activities of the new effort in interpretability for scientific discovery. Help track workstreams, milestones, and deliverables, and raise issues to senior staff when needed.
• Assist in developing the group’s research roadmap and priorities so they align with broader laboratory goals.
• Serve as a primary hands-on contributor to research and engineering across group projects, helping keep technical quality consistent.
• Develop tutorials and onboarding materials, and organize regular group check-ins and technical discussions, so new members ramp up quickly and knowledge is shared.
• Implement and apply mechanistic interpretability techniques to scientific foundation models and AI systems. These include feature discovery, sparse dictionary learning, circuit analysis, probing, and activation steering.
• Help investigate how models trained on scientific data represent physical, chemical, and materials concepts, and assist in evaluating how reliable interpretability methods are in these settings.
• Build and maintain reusable tooling, pipelines, and GPU-accelerated workflows for interpretability experiments.
• Support foundation model training, agentic oversight frameworks, and autonomous laboratory efforts as part of a broader team working on scientific automation.
• Contribute to high-priority laboratory initiatives as assigned, including Globus GPU-accelerated inference, ISAAC and other Genesis programs, Terminal-Bench Science, and new laboratory and industry collaborations.
• Contribute developing, deploying, and managing data infrastructure services, including systems for publishing large datasets in materials science, chemistry, and other domains.
• Help define and document requirements and architecture for secure, scalable, asynchronous data access services.
• Develop, test, document, and maintain software on a cloud-based platform, including REST, command-line, and socket-based interfaces. Apply GitOps principles for reproducible deployments.
• Work with other development teams to integrate cross-service features, and troubleshoot day-to-day technical problems using standard procedures.
• Under the guidance of the Principal Investigator, support external engagement, including partnership discussions, technical meetings, and relationships with program managers and collaborators.
• Help identify real-world applications for the group’s technologies, and contribute ideas for new projects or exploratory efforts.
• Performs code testing on components and works to ensure that appropriate implementation standards are met.
• Investigates and resolves day-to-day technical problems using standard procedures.
• Performs other related work as needed.

Minimum Qualifications

Education:

Work Experience:

Certifications:

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Preferred Qualifications

Experience:

• Relevant experience in related job discipline may include: Research internships, research assistantships, or co-op positions in machine learning, AI interpretability, computational science, or software engineering. Internship experience at a national laboratory, academic research group, or industry AI lab is strongly valued.
• Hands-on work on research projects involving large language models, scientific foundation models, or other deep learning systems, including undergraduate or graduate thesis work, published conference papers and preprints.
• Contributions to open-source software projects, particularly in machine learning, interpretability tooling, or scientific computing.
• Experience developing, testing, and deploying software in a collaborative team setting, whether through internships, research groups, or professional roles.
• Exposure to research outputs such as co-authored papers, workshop submissions, technical reports, posters, or conference presentations (preferred but not required).

Technical Skills or Knowledge:

• Experience developing code in Python, with knowledge of Node.js and/or a compiled language such as C/C++.
• Experience with deep learning frameworks such as PyTorch or JAX, and familiarity with model libraries such as Hugging Face Transformers.
• Familiarity with mechanistic interpretability methods, including sparse autoencoders or dictionary learning, probing, circuit analysis, activation patching, or activation steering. Experience with tools such as TransformerLens, nnsight, or SAELens is a plus.
• Understanding of transformer architectures and how large language models and scientific foundation models are trained and evaluated.
• Experience running GPU-accelerated workloads, including on HPC clusters or cloud GPU instances, and familiarity with job schedulers such as Slurm (strongly preferred).
• Knowledge of cloud computing platforms (AWS, GCP, Azure, etc.).
• Proficiency in software development best practices, including version control (Git), code review, testing, documentation, and CI/CD pipelines.
• Experience building or consuming REST APIs and command-line tools; familiarity with asynchronous or socket-based interfaces is a plus.
• Experience with data science and analysis tools (NumPy, pandas, scikit-learn, Jupyter) and with handling large datasets.
• Interest in or exposure to scientific domains such as materials science, chemistry, catalysis, or x-ray science (preferred but not required).

Preferred Competencies

• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills in English.
• Ability to work effectively in a dynamic, hybrid work environment, collaborating with other team members.
• Interest in and experience developing software to support data-driven research.

Working Conditions

• Remote work options are available for this position, with occasional attendance required at in-person meetings.

Application Documents

• Resume/CV (required)

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When applying, the document(s)MUST be uploaded via theMy Experience page, in the section titledApplication Documents of the application.

Job Family

Role Impact

Scheduled Weekly Hours

Drug Test Required

Health Screen Required

Motor Vehicle Record Inquiry Required

Pay Rate Type

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FLSA Status

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Pay Range

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

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 theBenefits Guidebook.

Posting Statement

The University of Chicago is an equal opportunity employerand 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 theUniversity's Notice of Nondiscrimination.

Job seekers in need of a reasonable accommodation to complete the application process should call773-702-5800 or submit a request viaApplicant 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.

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