About the role
This is a rare opportunity to deploy models with real purpose, where better underwriting and smarter automation translate directly into access to credit for people the traditional system overlooks. We're looking for a Senior Founding AI/ML Engineer to design, build, and ship the machine learning and AI-powered features at the core of our lending platform, and to own their lifecycle from prototype to production. You'll bring strong problem-solving skills, a collaborative spirit, and a passion for robust, scalable, production-grade models - plus the pragmatism to roll up your sleeves on the engineering needed to get them live. You'll work closely with experienced leaders, a cross-functional team, and our vendor partners.
Because lending is a regulated domain, model interpretability, explainability, and fairness aren't nice-to-haves - they're central to the job.
The compensation for this role is pay + equity. Flexible New York City remote/hybrid. Full time.
What you'll own
- Design, build, and deploy production ML models across the lending lifecycle: credit risk and underwriting, fraud and identity signals, and cash-flow-based decisioning.
- Build AI-powered product features: LLM/RAG systems for borrower support and document understanding (e.g., KYC and income documents), plus internal tooling that makes the team faster.
- Own the full model lifecycle: data and feature engineering, prototyping, production deployment, monitoring, and retraining.
- Make models trustworthy and compliant: explainable predictions, fair-lending awareness, and clear model documentation and governance.
- Integrate models into the Django backend and expose them through the API, partnering with the full-stack engineer so features ship end-to-end.
- Turn a multi-vendor data surface (including credit, cash-flow, and identity data) into reliable features and signals.
Preferred
- Experience designing and supporting the AI/data-science model lifecycle in fintech - from architecture and prototyping through to production-grade code and application integration, alongside the engineering team.
- Credit risk, underwriting, or cash-flow modeling experience.
- Familiarity with fair-lending, model-risk management, or regulatory requirements (e.g., ECOA / Reg B adverse action).
- Familiarity with MLOps platforms and model serving infrastructure.
- Applied mathematics background - discrete mathematics, complex systems, and mathematical modeling.
- Strong understanding of data structures and distributed systems for large-scale data processing, with an eye for efficient, scalable algorithm and code design.
Qualifications
- Technical experience as a lead ML engineer, VP of Machine Learning, senior staff ML engineer, principal applied scientist, founding AI/ML engineer, CTO, or similar.
- 6+ years of experience designing, building, and deploying production-grade machine learning models and AI systems, including technical leadership.
- Deep proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, scikit-learn).
- Experience with NLP, LLMs, and RAG architectures.
- You care deeply about model interpretability and explainability, and about building systems that users, teammates, and regulators can trust.
- Working proficiency with our application stack - Python and Django (Django REST Framework) - enough to ship your own models into production; comfort with TypeScript/Next.js is a plus.
- Strong data science foundation, including hands-on experience with statistical modeling, experimentation, and translating insights into decisions.
- Strong hands-on experience with AWS (configuring, not just deploying).
- Strong familiarity with GIT, CI/CD pipelines and automated deployment.
- Strong command of AI coding tools, with disciplined verification and data-privacy guardrails - you'll be handling sensitive financial and personal data.
- Excellent documentation skills and a commitment to organized, understandable code that scales as the team grows.
- Curiosity about fintech + empathy for users (you are passionate about building technology that solves real-world financial challenges).
- Comfortable in a lean, early-stage environment with high ownership (hands-on, end-to-end builder across the stack); you are a self-starter who builds without needing constant oversight.
- You thrive in fast-paced environments and are excited about pushing AI from research into production.
- Flexible New York City hybrid
- Master’s degree or PhD in computer science, data science, engineering, or similar.
- Background check, in-person New York interview, and references required.
Preferred
- Experience designing and supporting the AI/data-science model lifecycle in fintech - from architecture and prototyping through to production-grade code and application integration, alongside the engineering team.
- Credit risk, underwriting, or cash-flow modeling experience.
- Familiarity with fair-lending, model-risk management, or regulatory requirements
- Familiarity with MLOps platforms and model serving infrastructure.
- Applied mathematics background - discrete mathematics, complex systems, and mathematical modeling.
- Strong understanding of data structures and distributed systems for large-scale data processing, with an eye for efficient, scalable algorithm and code design.
Why Join LendKoi?
LendKoi is a financial technology company that provides credit and a digital financial suite for immigrants. We're on a mission to empower individuals to achieve stability and thrive. We're an early-stage startup backed by Techstars NYC and top angels with an incredible team.
Mission-driven
Be part of a mission to provide fair and accessible credit and unlock opportunities underbanked communities.
At The Frontier
Join a company at the frontier of consumer financial technology, credit, and payments.
High-impact role
You will shape how thousands first experience and understand us.
Creative Freedom
Test ideas, iterate quickly, and bring personality to fintech.
Small, fast team
You’ll work closely with the executive team, with plenty of ownership.
Learn a Ton
From incredibly talented leaders, and genuinely good people; trust and integrity are at the core of how we operate.
Paid, full-time, flexible hybrid
Paid, full-time, flexible hybrid role