Real-Time AI/ML Engineer for Legal NLP & Equity

eNZeTi; Huntington Beach (CA); Híbrido; USD 160.000 - 280.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity

Descripción de la vacante

eNZeTi is hiring for a senior ML role to own the full ML stack, from data pipelines to inference infrastructure, for real-time law firm intake calls. You will ship models in production with sub-200ms latency and directly influence coaching prompts and scoring after each session.

You will work with the founding team to deploy transformer models, optimize latency, and scale ML architecture as the customer base grows. Equity is part of the package.

Formación

• 3+ years shipping production ML systems.
• Real-time audio, speech, or conversational AI experience.
• Strong Python, PyTorch or TensorFlow, and AWS skills.
• Understanding of intent classification, NER, and dialogue systems.
• Experience optimizing model inference for latency-sensitive production.

Responsabilidades

• Design and build real-time NLP pipelines for live intake call analysis.
• Train and fine-tune transformer models on legal intake conversation data.
• Engineer sub-200ms inference pipelines for in-ear real-time coaching delivery.
• Build post-call scoring models that grade coordinator performance across 10+ dimensions.
• Own model evaluation, quality metrics, and continuous improvement loops.
• Collaborate with backend engineering on streaming audio architecture.
• Define the long-term ML architecture as data volume and customer base scale.
• Mentor future ML team hires as the engineering org grows.

Conocimientos

Real-time ML systems

Production ML shipping

Speech/Conversations AI

Herramientas

Python

PyTorch

TensorFlow

AWS

Descripción del empleo

eNZeTi is hiring for a senior ML role to own the full ML stack, from data pipelines to inference infrastructure, for real-time law firm intake calls. You will ship models in production with sub-200ms latency and directly influence coaching prompts and scoring after each session.

You will work with the founding team to deploy transformer models, optimize latency, and scale ML architecture as the customer base grows. Equity is part of the package.