Cognitive Scientist

Circle Labs; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive pay

Equity

Health coverage

AI Engine access

Job summary

Circle Labs in San Francisco is seeking a researcher to study how people and AI shapes think, make, and spend time together. You will investigate attention, trust, shared understanding, and participation in human–AI groups, turning evidence into practical evaluation and improvement strategies for shapes.inc.

Work with designers and engineers to translate findings into prototypes and evaluations of conversational behavior, and communicate findings to guide concrete product decisions and follow-up

Qualifications

• Proven experience in designing and executing cognitive science/psychology studies.
• Ability to combine qualitative and quantitative data.
• Experience recognizing confounds and avoiding overstated causality.
• Experience communicating findings to non-specialists.
• Proficiency with Python, R, or equivalent research tools.

Responsibilities

• Study delegation effects on trust, accountability, participation, and belonging.
• Design and run studies using experiments, interviews, surveys, and observation with clear hypotheses and consent.
• Compare collaboration with one assistant vs. teams of agents; measure shared understanding and coordination.
• Analyze outcomes for groups and individuals, accounting for relationships and repeated interactions.
• Collaborate with AI interactions designers and engineers to translate findings into prototypes and assessments.
• Communicate findings and limitations in briefs guiding product decisions and follow-ups.

Skills

Cognitive science research

Experimental design

Statistical analysis

Qualitative methods

Stakeholder communication

Tools

Python

R

Job description

About Circle Labs

Circle Labs is the company behind shapes.inc, a place to collaborate. We’re building multiplayer AI: shapes are collaborative assistants that take part in group conversations and do things with you and your people. Our next work includes helping groups set shared goals, delegate to specialist shapes and external agents, and follow progress through to completion. Making things, figuring things out, and sharing plans give people more reasons to spend time together.

We’re a small team in San Francisco. We use the product every day, talk to users, and work across design, engineering, and research.

About the role

Study what happens when people and shapes think, make, and spend time together. You will investigate attention, trust, shared understanding, and participation in human–AI groups, then turn that evidence into practical ways to evaluate and improve collaboration in shapes.inc.

What you’ll do

• Study how delegation among people and agents affects trust, accountability, participation, and people’s sense of belonging.
• Design and run studies using experiments, interviews, surveys, and observation, with clear hypotheses and appropriate participant consent.
• Compare collaboration with one assistant and teams of specialist agents, measuring shared understanding, coordination effort, goal completion, and whether people understand who is responsible for decisions and actions.
• Analyze outcomes for whole groups as well as individual participants, accounting for relationships between participants, repeated interactions, and uncertainty in the results.
• Work with AI interactions designers and engineers to translate findings into prototypes and evaluations of conversational behavior.
• Communicate findings, limitations, and alternative explanations in research briefs that guide concrete product decisions and follow-up studies.

What you’ll bring

• Research experience in cognitive science, psychology, human–computer interaction, behavioral science, or a closely related area.
• Practical command of experimental design, measurement, and statistical analysis, including how to recognize confounding and avoid overstating causality.
• Experience running studies with people and combining quantitative results with qualitative evidence.
• The ability to analyze data reproducibly using tools such as Python, R, or an equivalent research environment.
• Clear examples of turning an open research question into a study, interpreting the results, and explaining their implications to people outside your specialty.

Nice to have

• Research on group cognition, joint attention, conversation, social computing, or collaboration with AI.
• Experience with longitudinal studies, field experiments, or analysis of interactions within groups.
• Experience building research prototypes or evaluation methods that designers and engineers can reuse.

Benefits

• Competitive pay and equity
• Health, dental, and vision coverage
• Access to frontier AI Engines