Product Manager, Legal Tech

Enzeti; Huntington Beach (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity - meaningful

Direct collaboration with founders

Job summary

A tech startup specializing in legal AI is hiring a Machine Learning Engineer in Huntington Beach, CA. You will be responsible for building real-time voice analysis models that enhance law firm intake calls. With your strong background in ML systems and real-time audio processing, you'll work closely with the founding team. This role offers significant equity and a chance to impact the legal assistance landscape directly. Join us to mentor future ML hires while automating coaching prompts in live scenarios.

Qualifications

• 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.

Responsibilities

• 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 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.

Skills

Production ML

Real-time AI

Python

PyTorch

TensorFlow

AWS

Latency optimization

NLP

NER

Dialogue systems

Founders collaboration

Tools

Transformers

Job description

Base salary range. Equity on top. Negotiable for the right person.

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.

You will own the full ML stack from data pipelines to inference infrastructure. You will define how eNZeTi detects objection patterns, surfaces coaching prompts, and scores calls post-session. The work is hard, the problem is real, and the impact is immediate. Law firms using eNZeTi convert 20-40% more cases. That starts with what you build.

What You Will Do

• 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

What We Need

• 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

What You Will Build On

• 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.

Team Product

Type Full-Time

Location Huntington Beach, CA

Equity Yes — meaningful

Reports To CTO / Founders

Ready to Apply?

Send your resume and a brief note on what you would build first.