Member of Technical Staff – Explainability Engineer (Alignment + SHAP)
Location: Austin, Texas
Department: Engineering
Location Type: REMOTE
Employment Type: FULL_TIME
- Design and implement SHAP-based explanation layers for GenAI outputs
- Architect AutoHeal interventions for misaligned model behavior
- Build alignment experiments grounded in real-world compliance datasets
- Own deployment of explainability dashboards for internal and customer usage
- MIT/Harvard (CS, EECS, HST) with strong research-to-production instincts
- Familiar with SHAP, LIME, or other explainability libraries
- Able to design alignment experiments that are both empirical and operational
- Thrive in ambiguity and ship aligned features end-to-end
- Founder-level ownership on compliance AI infra
- A deep technical legacy in one of GenAI’s most urgent domains
- Equity in a company built to define real-world alignment
- A public portfolio of traceable, explainable AI systems
- Compensation: Salary + equity
- Commitment: Full-time or intense part-time (15+ hrs/week)
- Start: Rolling (ideal: within 2–4 weeks)
- To Apply: Tell us how you'd extend SHAP to make multi-modal outputs traceable
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