Senior ML Explainability Engineer — Remote + Equity

Elloe AI; Austin (TX); Hybrid; USD 180.000 - 260.000; Vollzeit

Benefits dieser Stelle

Real equity

Remote-first

Zusammenfassung

Elloe AI is the trust layer for AI, and this Staff ML Systems Engineer role owns the explainability stack used to inform deployment decisions. You’ll build SHAP overlays that run in production with sub-100ms latency and real trace logs, tied to actual decisions.

We expect you to ship ML infrastructure at real-world scale, reason about SHAP limits, and collaborate across policy, risk, and product to ensure compliance and auditable outputs.

Qualifikationen

• Shipped ML infra at scale with real latency targets.
• Knowledge of SHAP and limitations, with practical workarounds.
• Ability to derive production-ready explainability from first principles.
• Experience explaining models to non-technical stakeholders.

Aufgaben

• Own the explainability stack used for production deployment decisions.
• Build SHAP overlays that run inline with model responses and are auditable.
• Integrate explainers across Claude, GPT-4 and Mistral with version control.
• Create dashboards, audit logs, and human-readable traces for compliance.

Kenntnisse

SHAP explainability

ML infra

Production latency

Retrieval explainability

Vector search

Tools

Claude

GPT-4

Mistral

Jobbeschreibung

Elloe AI is the trust layer for AI, and this Staff ML Systems Engineer role owns the explainability stack used to inform deployment decisions. You’ll build SHAP overlays that run in production with sub-100ms latency and real trace logs, tied to actual decisions.

We expect you to ship ML infrastructure at real-world scale, reason about SHAP limits, and collaborate across policy, risk, and product to ensure compliance and auditable outputs.