Founding Research Scientist: Building Experience-Based AI

Observable Intuition, Inc.; New York, Northern (NY, KY); Hybrid; USD 120,000 - 250,000; Full time

Benefits offered by this job

Equity

Job summary

Observable Intuition is building the infrastructure that makes human experience observable, learnable, and actionable by AI. Based in San Francisco and New York, we’re seeking a Founding Research Scientist to define the research foundations behind this new layer of intelligence.

You’ll work with a founding team to develop methods, build working systems, and guide long-term technical direction, deploying research into real enterprise environments with rigorous evaluation.

Qualifications

• PhD in ML, statistics, CS, or related field.
• Research in graph ML, knowledge representation, temporal/event modeling, or uncertainty quantification.
• Strong statistical foundations and model evaluation.
• Experience building learning systems with weak supervision.
• Ability to deploy research ideas into production systems.

Responsibilities

• Build models transforming noisy observational data into structured representations.
• Develop methods to learn organizational behavior from real-world activity.
• Model how state and behavior evolve over time.
• Design uncertainty estimation and calibrated abstention systems.
• Create evaluation methodologies for data-sparse problems.
• Take research into deployed systems with scientific rigor.
• Collaborate with founders to shape research direction and roadmap.

Skills

Graph machine learning

Knowledge representation

Temporal modeling

Uncertainty quantification

Education

PhD in ML/CS/Statistics

Tools

PyTorch

JAX

Job description

Observable Intuition is building the infrastructure that makes human experience observable, learnable, and actionable by AI. Based in San Francisco and New York, we’re seeking a Founding Research Scientist to define the research foundations behind this new layer of intelligence.

You’ll work with a founding team to develop methods, build working systems, and guide long-term technical direction, deploying research into real enterprise environments with rigorous evaluation.