Note: The job is a remote job and is open to candidates in USA. LendKoi is a fintech company focused on providing access to credit for underserved populations. They are seeking a Senior AI/ML Engineer to design, build, and deploy machine learning and AI-powered features for their lending platform, overseeing the entire model lifecycle from prototype to production.
Responsibilities
- 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
Skills
- 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
- 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
Benefits
- The compensation for this role is pay + equity.
- Flexible New York City remote/hybrid.
- Full time.
Company Overview