Founding ML Engineer / Founding Full-Stack AI Engineer

Location: Onsite San Francisco, CA (South Park)
Position Type: Full-Time (Permanent)
Work Policy: In-person (no remote) Visa sponsorship considered case-by-case
Start Timeline: ASAP

About
This early-stage AI startup is building a digital account manager agent that autonomously analyzes data, surfaces revenue insights, and automates follow-through. The goal is to multiply the output of every customer-facing team and unlock billions in untapped enterprise revenue. With $2M in pre-seed funding, this is a rare opportunity to join at the earliest stage and build foundational technology in a massive market.

Why join

• Architect, build, and scale a platform from 0 to 1 in an under-tapped, high-value market

• Work directly with founders in a high-autonomy, high-agency role

• Above-market ownership, equity, and cash compensation for A-players

• Massive upside potential via ARR-based cash bonus program

• High-velocity environment 3-interview process with potential to close in one week

Compensation

• Base Salary: $150,000 - $250,000

• Equity: 1% - 2%

• Bonus: For every $1M in ARR achieved within the first 12 months, a cash bonus equal to base salary will be paid (no cap)

• Notes: Above-market compensation available for top talent

Tech environment

• Languages: TypeScript, Python, React

• Focus: Applied ML, enterprise-scale integrations, data ontology mapping, agentic AI solutions, production ML pipelines

Role summary
As a Founding Engineer, you will own and ship features end-to-end, from architecture to deployment. You will shape the product roadmap, develop customer-facing AI solutions, and iterate rapidly based on real-world feedback.

Responsibilities

• Architect and implement integrations and data ontology mapping tools for enterprise-scale ingestion and normalization of third-party data

• Develop and maintain immersive UIs for AI-driven workflows (beyond basic chatbots)

• Build agentic solutions that automate complex workflows, incorporating long-term agent memory and reinforcement learning enhancements

• Work closely with customers to iterate on solutions that drive measurable revenue outcomes

Must-have qualifications

• 3-6 years of applied ML engineering experience

• Proven 0-to-1 product delivery with measurable customer impact

• Experience with TypeScript, Python, and React

• Undergraduate degree in Computer Science from a top-30 school

• Production ML pipeline experience

• Strong grasp of ML/statistics/math fundamentals

• Deep understanding of ML models and selection for real-world use cases

• Startup experience and willingness to work in-person in San Francisco at an early-stage company

Preferred qualifications

• Balanced experience in applied ML and full-stack development

• Strong production-ready track record beyond research or infrastructure-only roles

• Ability to iterate rapidly in real-world startup conditions