Remote-friendly Multiagent Coordination Scientist

HushOne, Inc.; Kirkland (WA); Hybrid; USD 120,000 - 190,000; Full time

Benefits offered by this job

Stock options

401(k) with company match

Health, dental & vision

Gym membership

Remote-friendly

Job summary

HushOne, Inc. is seeking a researcher to advance coordination in distributed AI, focusing on how independent agents negotiate while preserving human boundaries.

The role emphasizes rigorous mathematical reasoning and experiments mapping to enforceable permissions. You will design a reproducible 90-day experiment with private constraints, partial information, and verification of results, collaborating with protocol engineers and identity teams.

Qualifications

• Research in distributed AI, game theory, multiagent learning, or coordination systems.
• Mathematical clarity and willingness to test a simpler alternative first.
• Reason about incentives and adversarial behavior, not just cooperation.
• Keep the human boundary intact in the formalism, not only in description.

Responsibilities

• Design a shared scheduling task with private constraints and one remote agent returning unreliable results.
• Collaborate with protocol and identity engineers to map coordination research to enforceable permissions.
• Produce a reproducible 90‑day experiment with explicit trust assumptions and comparisons.

Skills

Distributed AI

Game theory

Multiagent learning

Incentive analysis

Coordination protocols

Education

PhD in CS/AI

Tools

Simulation frameworks

Job description

HushOne, Inc. is seeking a researcher to advance coordination in distributed AI, focusing on how independent agents negotiate while preserving human boundaries.

The role emphasizes rigorous mathematical reasoning and experiments mapping to enforceable permissions. You will design a reproducible 90-day experiment with private constraints, partial information, and verification of results, collaborating with protocol engineers and identity teams.