Member of Technical Staff – AI Research Engineer (Explainability & Alignment)

Elloe AI; Austin (TX); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Salary + equity

Job summary

Elloe AI is seeking a Member of Technical Staff – AI Research Engineer to own SHAP-driven explainability and alignment systems for GenAI in regulated industries. You will design SHAP-based explanations, run alignment experiments, and deploy explainability dashboards for internal and customer use.

Role requires strong research-to-production instincts, familiarity with SHAP/LIME, and the ability to ship aligned features end-to-end in a remote, full-time setting.

Qualifications

• Strong research-to-production instincts with MS/PhD in a relevant field.
• Experience designing SHAP-based explanations and model alignment.
• Ability to ship explainability features and dashboards end-to-end.

Responsibilities

• Design SHAP-based explanation layers for GenAI outputs.
• Architect AutoHeal interventions for misaligned models.
• Build alignment experiments grounded in real-world data.
• Own deployment of explainability dashboards for internal and customer use.

Skills

SHAP

LIME

Explainability libraries

Alignment experiments

End-to-end deployment

Education

PhD in CS/EECS or related

Tools

SHAP

LIME

Job description

Member of Technical Staff – AI Research Engineer (Explainability & Alignment) at Elloe AI

Type: Full-time | Location: Remote | Function: Alignment & Explainability | Reports to: CTO/CEO

About Elloe AI

Elloe is building the immune system for AI. We help organizations in healthcare, finance, and policy deploy GenAI systems that are explainable, auditable, and safe. Our stack fuses SHAP explainability, secure Vault sync, and red-team simulation defense — all built by engineers from MIT and Harvard.

About the Role:

You’ll own the design of SHAP-driven explainability and model alignment systems for GenAI in high-stakes industries. From human-in-the-loop correction to production-grade dashboards, you’ll architect and ship the critical loops that make AI traceable, safe, and compliant. for real-world GenAI. This means SHAP-layer visualizations, alignment experiments with AutoHeal, and deeply integrating human feedback into every model correction. You’ll own core loops that power how Elloe learns to heal itself.

What You’ll Own

• 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

Who You Are

• 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

Why Now

GenAI is entering regulated sectors faster than governance can keep up. AutoHeal v4.2 is Elloe’s leap toward traceable, compliant AI — just as hospitals, banks, and policy orgs realize they need it. This is the right mission at the right moment.

You’ll Leave This Role With

• 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

Logistics & Application

• Compensation: Salary + equity
• Commitment: Full-time or intense part-time (15+ hrs/week)
• Start: Rolling (ideal: within 2–4 weeks)