--- title: 'Staff Machine Learning Engineer at Kikoff' canonical: 'https://feeny.ai/job/staff-machine-learning-engineer-kikoff-san-francisco-ptnbmmfqvgvf' type: 'job' last_seen: '2026-09-11' --- # Staff Machine Learning Engineer at Kikoff - **Company:** Kikoff - **Location:** San Francisco, CA - **Compensation:** $307k–$352k - **Posted:** 2026-09-05 - **Last confirmed live:** 2026-09-11 - **Apply:** https://job-boards.greenhouse.io/kikoff/jobs/4396892009 ## Job description Kikoff: The Fintech Powering Financial Security at Scale Kikoff is a profitable, pre-IPO fintech company on a mission to empower everyone to achieve financial security. With record revenue growth in 2025 and a unicorn valuation, we've built a suite of products that help millions of people build credit, access liquidity, and save money. We're scaling fast. Join us if you want to build something meaningful and help millions of people move forward financially. Why Kikoff: This is a consumer fintech startup, and you will be working with serial entrepreneurs who have built strong consumer brands and innovative products. We value extreme ownership, clear communication, a strong sense of craftsmanship, and the desire to create lasting work and work relationships. Yes, you can build an exciting business AND have real-life real-customer impact. About the role: We are seeking a Staff Machine Learning Engineer to set the technical direction for machine learning at Kikoff. ML sits at the center of our business: our underwriting models decide who we extend credit to, our risk models protect our customers and our balance sheet, and our personalization and growth models shape how millions of people experience our products. As a Staff engineer, you will own the ML platform and modeling roadmap end to end. You will decide how we build, evaluate, ship, and govern models across the company, lead the highest-leverage and most ambiguous projects yourself, and raise the bar for every engineer who works on ML here. This is a hands-on role with company-level impact, not a management track. Key Responsibilities: - Technical Strategy and Roadmap: Define the multi-quarter vision for ML at Kikoff, spanning underwriting, fraud and risk, and personalization. Identify where ML creates outsized business value, size the opportunity, and drive alignment with Product, Risk, Finance, and Engineering leadership. - ML Platform Ownership: Architect and evolve the platform that every model at Kikoff runs on: feature stores, training and evaluation pipelines, model registry, real-time and batch serving, and monitoring. Make build-vs-buy decisions and set the standards for how ML systems are designed, tested, and operated in production. - Flagship Model Development: Personally lead the most consequential modeling work, including our cash advance and credit underwriting models. Own the full lifecycle from problem framing and data strategy through validation, launch, champion/challenger testing, and iteration. - Model Risk and Governance: Partner with Risk, Compliance, and Legal to establish model governance fit for a lender at our scale: documentation, fair-lending and disparate-impact analysis, explainability, validation standards, drift and performance monitoring, and audit readiness. Ensure our models are defensible to regulators and to ourselves. - Experimentation and Measurement: Set the standards for how ML changes are tested and measured, including experiment design, guardrail metrics, and the link between offline evaluation and realized business outcomes such as loss rates, approval rates, and customer lifetime value. - Cross-Functional Leadership: Act as the technical counterpart to product and business leaders on ML initiatives. Translate ambiguous business goals into concrete technical bets, and communicate tradeoffs, risks, and results clearly to executives and non-technical stakeholders. - Technical Leadership and Mentorship: Raise the engineering bar across the ML and data organizations through design reviews, code reviews, and hands-on mentorship. Grow senior engineers into technical leaders, and help shape hiring and team structure as the ML function scales. Qualifications: - Experience: 8+ years of software or machine learning engineering experience, including 5+ years building, deploying, and operating ML systems in production. Prior experience as a technical lead or the most senior ML engineer on a team. - Track Record: Demonstrated ownership of ML systems with direct, measurable business impact at scale. Experience in consumer lending, credit underwriting, fraud, or payments strongly preferred. - Technical Depth: - Expert-level Python; strong general software engineering fundamentals and system design skills. - Deep experience with the full ML lifecycle in production: feature engineering, training, evaluation, serving (batch and real-time), monitoring, and retraining. - Hands-on experience designing ML platform components such as feature stores, model registries, and evaluation frameworks, and making pragmatic build-vs-buy decisions. - Strong command of gradient-boosted trees and classical ML for tabular data; working knowledge of deep learning frameworks (e.g., PyTorch) where applicable. - Production experience with cloud infrastructure (AWS or GCP), containerization (Docker, Kubernetes), and modern MLOps and CI/CD tooling. - Experience working alongside Ruby/Rails backends is a plus. - Model Risk Fluency: Understanding of model governance in a regulated financial environment, including fair lending considerations, explainability, and model validation practices. Experience working with Risk or Compliance partners on model approval processes is a plus. - Analytical Rigor: Exceptional ability to frame ambiguous problems, design sound experiments, and reason carefully about causality, selection bias, and the gap between offline metrics and real-world outcomes. - Leadership and Communication: A history of influencing technical direction beyond your immediate team without formal authority. Able to explain complex modeling decisions and their business implications crisply to executives, and to mentor engineers at all levels. - Educational Background: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. Advanced degree preferred. Base Range $307,000—$352,000 USD ## Equal Employment Opportunity Statement Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. Please reference the following for [more information](https://www.eeoc.gov/sites/default/files/2022-10/22-088_EEOC_KnowYourRights_10_20.pdf). ## About Kikoff ## Company Overview - **One-liner**: Kikoff is a personal financial technology company that builds credit, manages debt, and unlocks financial opportunity for underserved consumers. - **Entity Type**: Private (Series C) - **Headquarters**: San Francisco, California, United States - **Founded**: 2019 - **Founders**: Cynthia Chen (CEO & Founder) ## Core Business - **Primary industry/industries**: Consumer Fintech, Credit Building, Personal Finance - **Target customers**: B2C – individuals seeking to build or improve credit scores, manage debt, and access affordable financial services. - **Mission or purpose statement**: Empowering everyone to achieve financial security, no matter where they’re starting from. ## Products & Services - **Credit Building ($5/month)**: A credit-builder loan that reports to major credit bureaus with no interest and no hidden fees. - **Rent & Bill Reporting**: Reports on-time rent and utility payments to credit bureaus to help users build credit from everyday bills. - **Secured Credit Card**: A card designed to help users establish or rebuild credit responsibly. - **AI-Powered Debt Negotiation**: Complimentary service that uses AI to negotiate debt reductions for users (over $8M in debt relief since 2024). - **Identity Theft Protection**: Monitoring and alerts for identity fraud. - **Fynn (AI Credit Coach)**: Launched in 2026, an AI-powered coach providing personalised financial guidance. - **Grant & Catch**: Additional products in the ecosystem (likely focused on grants and savings/catch-up features). ## Market Standing - **Valuation/Market Cap**: Not publicly disclosed (unicorn status inferred from growth and investor profile). - **Key Metric**: Annual Revenue surpassed **$300M** in 2025, more than doubling year over year while maintaining profitability since 2023. - **Total Raised**: $42.5M (Series C) - **Notable Investors**: Core Innovation Capital, Coatue, Lightspeed, Portage, Notable Capital (and 12+ others) - **Growth Signals**: Profitable since 2023; reached $300M+ revenue in <7 years; 1M+ customers; 80M+ credit points boosted; 30K+ mortgages and 433K+ auto loans opened after using Kikoff; appointed CFO John Kaelle and CLO Robert Mahnke in 2026, signalling public-market readiness. ## Competitive Advantages - **Radically affordable pricing** ($5/month for credit building vs. industry $300+) removes barriers for low-income users. - **AI-first approach** for debt negotiation and credit coaching creates scalable, personalised solutions. - **Proprietary technology** builds the entire stack in-house, lowering costs and enabling faster iteration. - **Strong unit economics** and profitability demonstrate operational discipline uncommon at this growth stage. ## Strategic Focus - **Continued product expansion** – adding new financial tools (Grant, Catch, Fynn) to create a one-tap financial security platform. - **Deepening leadership bench** with IPO-experienced executives to prepare for future public listing. - **Investing in AI and automation** to replace legacy systems and deliver faster, more accessible outcomes. - **Scaling customer impact** – targeting underserved millions through low-cost, high-access offerings. ## Why Work Here - **Mission-driven culture** with real impact: 1M+ customers helped, $8M in debt relief, 80M+ points boosted. - **Financial stability** – profitable since 2023 with rapid revenue growth, reducing risk of layoffs. - **Strong values in action**: "Company First, Ego Last", "Act Like an Owner", "Customer Obsessed", "Think in Years, Act Today", "Be Candid & Kind". - **Comprehensive benefits**: Health benefits, flexible PTO, 401k matching, commuter benefits, fitness benefit, office lunches & dinners. - **Hybrid/Office setting** in San Francisco (132 Hawthorne Street) – likely a collaborative in-office culture with team meals. - **Growth trajectory** – team is "growing rapidly" (as stated on careers page), offering ample career advancement opportunities. - **Engineering and AI focus** – investing heavily in technology, making it an exciting environment for engineers and product builders. ## Sources 1. [about.kikoff.com/careers](https://about.kikoff.com/careers) 2. [about.kikoff.com/company](https://about.kikoff.com/company) 3. [cbinsights.com/company/kikoff](https://www.cbinsights.com/company/kikoff) 4. [businesswire.com](https://www.businesswire.com/news/home/20260421425245/en/) ## Other roles at Kikoff - [Growth Marketer](https://feeny.ai/job/growth-marketer-kikoff-san-francisco-z6qfyqyv9v1h) — San Francisco, CA - [Accounting Manager](https://feeny.ai/job/accounting-manager-kikoff-san-francisco-35fan94cvwqg) — San Francisco, CA - [Senior Mobile Engineer – Kikoff Main App](https://feeny.ai/job/senior-mobile-engineer-kikoff-main-app-kikoff-san-francisco-0wzv43tw9hbe) — San Francisco, CA - [Senior Security Engineer, Data Security](https://feeny.ai/job/senior-security-engineer-data-security-kikoff-san-francisco-s22nr407yw3d) — San Francisco, CA - [Software Engineer - Recent Grad](https://feeny.ai/job/software-engineer-recent-grad-kikoff-san-francisco-nz2587cvgzsn) — San Francisco, CA - [Staff Engineer - Web Applications](https://feeny.ai/job/staff-engineer-web-applications-kikoff-san-francisco-b1se2c71h5kj) — San Francisco, CA - [Senior Program Manager, Customer Experience](https://feeny.ai/job/senior-program-manager-customer-experience-kikoff-san-francisco-ffsx4x3hfeet) — San Francisco, CA - [Creative Operations Short Term Employee](https://feeny.ai/job/creative-operations-short-term-employee-kikoff-san-francisco-7fsvaxteh883) — San Francisco, CA - [Director, Securities & Corporate Counsel](https://feeny.ai/job/director-securities-corporate-counsel-kikoff-san-francisco-389rtj4q1v7g) — San Francisco, CA - [Product Counsel](https://feeny.ai/job/product-counsel-kikoff-san-francisco-gk0zewcryx3f) — San Francisco, CA