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
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