layiq

/la·yiq/adjective

worthy; deserving; fitting; suitable.

A role, opportunity, or path that merits attention, time, and pursuit.

Second Look Program Lead at University of Chicago | LAYIQ

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.

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.
Job Family
Research
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

Second Look Program Lead

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