Founding ML Engineer — Build AI-Driven Document Automation

Praxis, Inc.

San Francisco (CA)

On-site

USD 180,000 - 240,000

Full time

14 days+
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Benefits offered by this job

Health insurance
Daily lunches
In-office barista

Job summary

Abacus is hiring its first Founding Engineer to own and expand the core machine learning engine behind Abacus. You’ll report directly to the co-founders and work in person from our SF office, with massive autonomy and influence over product and technical direction.

In your first 3–6 months, you’ll scale the ML extraction engine using LLMs and OCR, own backend architecture, and ship greenfield features to expand automated workflows for tax firms. This is a rare growth opportunity.

Qualifications

  • 1–5 years of backend software experience, ideally in high-ownership or early-stage environments.
  • Strong backend development skills, particularly in Python.
  • Proven 0→1 builder (side projects, startup experience, or both).
  • Willingness to work from our SF office, 5 days/week.
  • Willingness to complete a technical take-home exercise as part of the process.

Responsibilities

  • Lead development of our ML-powered document extraction engine.
  • Architect backend systems with performance and scalability in mind.
  • Build and deploy new automation features for tax firms.
  • Collaborate closely with the founders on product and user needs.
  • Help define our engineering culture and technical roadmap.

Skills

Python
Backend development
0→1 builder

Tools

LLMs
OCR
Data extraction systems

Job description

Abacus is hiring its first Founding Engineer to own and expand the core machine learning engine behind Abacus. You’ll report directly to the co-founders and work in person from our SF office, with massive autonomy and influence over product and technical direction.

In your first 3–6 months, you’ll scale the ML extraction engine using LLMs and OCR, own backend architecture, and ship greenfield features to expand automated workflows for tax firms. This is a rare growth opportunity.

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