Second Look Program Lead

Second Look Program Lead

The Second Look Program Lead co-founds and co-leads Second Look, a new XLab research program dedicated to producing replications and verifications of influential AI safety research. Working alongside the existing founding Program Lead, this role shares responsibility for the research agenda, the fellowship cohort, the quality of published replications, and the program's external reputation. The Program Lead is expected to take technical ownership over a subset of replications, mentor fellows, set and enforce quality standards for publications, and represent the program publicly to the AI safety research community. Because Second Look is new, the Program Lead will also help shape the program's long-term direction, including co-owning fundraising and evaluation efforts that will determine whether Second Look continues as a permanent XLab team after the pilot. This position is expected to last approximately 12 months, but may be extended based on grant funding.

Responsibilities:

• Manages the replication selection process, working with XLab leadership, the other Program Lead(s), and the broader AI safety community to identify high-priority papers using Second Look's published criteria (narrative influence, research dependence, vulnerability, difficulty, and recency).
• Co-leads the Summer 2026 Fellowship cohort, including fellow supervision, weekly check-ins, and quality review of draft replications and write-ups.
• Takes direct technical ownership for a subset of replications, contributing to experimental design, implementation review, and publishable write-ups.
• Sets and enforces publication standards for Second Look outputs including the website, LessWrong crosspostings, code and artifact releases, and communications with original paper authors consistent with Second Look's commitment to fair, balanced, and accurate replications.
• Represents Second Look externally at conferences, in online research forums, and in direct conversations with senior researchers in the AI safety community.
• Responsible for fundraising and sustainability planning, including drafting grant proposals, briefing funders, and building the case for a permanent team after the pilot.
• Partners with the Second Look Operations Manager on program logistics and with the XLab administrative team on broader XLab operations.
• Helps recruit and vet future full-time staff, research engineers, and fellows for Second Look.
• Applies research principles and relevant subject matter knowledge relevant to administer a research project. With a moderate level of direction, manages lab and/or research-related duties and tasks. Helps develop, design and conduct research projects according to plan.
• Supports data collection and analytical needs of research projects. Conducts literature reviews and helps write reports and manuscripts. Ensures project compliance with different policies, procedures, directives, and mandates.
• Takes responsibility for the following non-laboratory duties: transcribing and coding data; developing data collection instruments; presenting research; and recruiting and scheduling research subjects. Acquires higher-level skills and knowledge in the process.
• Perform 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 2-5 years of work experience in a related job discipline.

Preferred Qualifications:

Education:

• Bachelor's or Master's degree in computer science, machine learning, statistics, or a related quantitative field.

Experience:

• Prior research experience in AI safety, machine learning, or a closely related technical field published work, fellowships (e.g., MATS, SERI MATS, ARENA, SPAR), or industry research experience.
• Experience managing or mentoring junior researchers.
• Experience writing for technical audiences papers, LessWrong/Alignment Forum posts, research blog posts, or similar.
• Demonstrated familiarity with the AI safety research ecosystem and its institutional landscape (frontier labs, independent research organizations, academic groups, funders).
• Experience contributing to or leading an open-source research project.

Preferred Competencies:

• Strong research taste: the ability to judge which claims in a paper are load-bearing and which are secondary.
• Excellent written and verbal communication, especially the ability to present technical critiques fairly and constructively.
• Comfortable working with a research community that has strong opinions and limited patience for sloppy work.
• Proficiency with Python, PyTorch, and common ML tooling; familiarity with evaluation frameworks and/or interpretability tooling is a plus.
• Comfort with Git, GitHub, and standard research engineering workflows.
• Judgment about when to publish, when to share findings with original authors first, and how to balance speed with rigor.

Working Conditions:

• In-person preferred; primarily based at the University of Chicago.
• May work occasional evenings and weekends, particularly around publication deadlines and external engagements.

Application Documents:

• Resume/CV (required)
• Cover letter (required)
• Links to representative technical writing, code, or prior research (preferred)
• References (preferred)

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