AI / ML Engineer

ENSET RESTAURANT LLC
Huntington Beach, CA, United States
4 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Cloud Computing Python (Programming Language) Tensorflow Pytorch Model Validation Machine Learning Operations Natural Language Understanding

Job description

You build the core of the product. Real-time voice analysis, in-call coaching triggers, post-call scoring. You will work directly with the founding team on the models that power every eNZeTi session. This is not a research position. Every model you ship runs in production during live law firm intake calls, coaching coordinators in real time. Sub-200ms latency is not a stretch goal. It is a requirement., * 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, * Real call data from active law firm customers - labeled, structured, growing daily
  • A founding team that understands AI deeply and will not slow you down
  • Greenfield ML infrastructure - no legacy debt, your architectural decisions stick
  • A clear roadmap from coaching prompts to predictive case outcome scoring

Why This Role Matters

94% of law firm intake calls go completely unreviewed. Coordinators get no feedback, no coaching, no real-time support on calls worth $5,000 to $50,000 in case value. What you build changes that. Every model improvement is a law firm that closes more cases, a coordinator who gets better at their job, and a client who actually gets the legal help they called about.

Requirements

  • 3+ years shipping production ML systems - not notebooks, not prototypes
  • Real-time audio, speech, or conversational AI experience (non-negotiable)
  • Python, PyTorch or TensorFlow, AWS or equivalent cloud infrastructure
  • Strong understanding of intent classification, NER, and dialogue systems
  • Experience optimizing model inference for latency-sensitive production environments
  • Ability to work directly with founders and ship without hand-holding

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