Careers at Kikoff

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. We are seeking a Senior Machine Learning Engineer to join our team. This role will focus on developing and maintaining machine learning infrastructure and operations, particularly for our cash advance underwriting model and other machine learning use cases. The ideal candidate will have a strong background in software development, machine learning, and data engineering, with experience in deploying scalable ML models in production environments. Key Responsibilities: ML Infrastructure and Operations: Design, build and maintain the infrastructure required for optimal extraction, transformation, and loading of data from various sources. Develop and manage data pipelines and workflows for machine learning models. Model Development and Deployment: Design, develop, and implement machine learning models for underwriting and other financial service applications. Ensure models are robust, scalable, and maintainable. Collaboration: Work closely with data scientists, software engineers, and product managers to integrate machine learning models into production systems. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Performance Monitoring: Monitor and evaluate the performance of deployed models, ensuring they meet the desired accuracy and efficiency metrics. Implement processes for continuous improvement and optimization of models. A/B Testing and Experimentation : Design and implement experiments to optimize models and ensure they align with business goals. Mentorship: Provide guidance and mentorship to junior engineers, fostering a culture of learning and growth within the team. Qualifications: Educational Background: Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field. Advanced degree preferred. Experience: Minimum of 3 years of experience in machine learning engineering, with a proven track record of deploying ML models in production environments. Technical Skills: Proficiency in programming languages such as Python or Ruby. Strong understanding of data structures, algorithms, and software design principles. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch). Familiarity with MLOps practices and tools for continuous integration and deployment of ML models. Experience with cloud services (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes). Analytical Skills: Strong problem-solving skills with the ability to analyze complex data sets, apply advanced data science techniques, and derive actionable insights. Proficient in building predictive models, performing statistical analysis, and utilizing machine learning algorithms to identify trends, patterns, and opportunities for optimization. Communication Skills: Excellent verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. What we’re like: - Scrappy . We had a product goal and put out the MVP, collecting our first users with steady growth via paid channels in four months. We don’t cut corners when we know we’ll need them but we don’t build things without that need. We don’t like inefficiency but we dislike operationalizing one-off tasks even more. - Risk-oriented . Everything has risk, but a mature team knows how to make these tradeoffs. That’s why we built the MVP fast––because time is your most valuable asset and is practically fungible with money in the startup world. - Data-obsessed . We all look at data and pull it, and we believe that understanding the mechanics can yield valuable insights. Complex systems require elegant, not just simple solutions. You absolutely need to be interested in data if you want to leverage your knowledge of systems. - Lucky . That’s how we look at this journey so far. From our timing of fundraising, to the circumstances in which we came together, to the initial product traction we’re getting, there’s no other word to describe it. We are grateful you are reading this, and we know that if you’re meant to be with us on this journey, then we will see you soon. Base Range $257,000 — $312,000 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 .

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 $336,000 — $392,000 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 .

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 Grant Grant is Kikoff's fastest growing business line. It started with earned wage access, solving the most common and most painful problem in consumer finance: short-term liquidity. Gas to get to work, an unexpected bill, groceries before the next paycheck. We give people fast, fair access to earned wages without the fees the industry has normalized, and we do it with a profitable business model. Since launching to the public at the start of 2025, Grant has grown from thousands to 900k+ active subscribers and has disbursed and recollected over $325M in cash advances. EWA is the core, and several new products are underway on top of it. Grant runs as its own business inside Kikoff, with a business lead and dedicated product, engineering, design, and marketing leads. About the Grant data science team Our job is to make sure every Grant product does three things: makes a clear and compelling promise to the customer, delivers on that promise reliably over time, and turns that durable value into a business healthy enough to fund the next product, in a way customers would agree is fair. Every metric we define, experiment we run, and model we build should trace back to one of those three. We're a team of three data scientists within Kikoff's Data organization, embedded full time with Grant. Each of us leads the data work for a product area and all of us take part in Grant-level roadmap and objective setting with Grant's business lead and the product, engineering, design, and marketing leads. About the role You'd be the fourth Data Scientist focused on the Grant business, and part of a larger Kikoff wide Data team. You'll take on a product area within Grant as its data lead, working day to day with the leads for that area, and you'll bring a staff-level view to the Grant-wide conversations on where the business goes next. Two things we're asking of this hire beyond the product area. First, help set technical direction and best practices for data science across Kikoff, not just Grant. Second, help define how we work as AI agents become a core part of the analysis loop, from exploration to pipelines to experiment readouts. We're actively rebuilding our workflow around this and want someone who has opinions. What you'll do Lead the data work for a Grant product area: set the questions worth answering, build the evidence, and drive what happens next. Sometimes the right call is not to act on a finding, and you'll make that case too. Define and maintain the measurement system for your product area (acquisition, activation, usage, repayment, losses, unit economics) and contribute to the Grant-wide measurement framework alongside the other data scientists on the team. Own product experimentation for your area: design, guardrails, analysis, and the recommendation on rollouts and policy changes (eligibility, limits, pricing), including changes where clean randomization isn't available. Build and evaluate models where they're the right tool: proof-of-concept and challenger models, offline evaluation, threshold and policy decisions, and production monitoring with engineering. The ML platform and production model lifecycle sit with our ML engineering team; how data and engineering divide that work is still evolving and you'll have a voice in it. Partner with Grant's business lead and the area leads on roadmap and objectives: which bets, what a win looks like, and what we'd need to see to stop. As a staff data scientist, contribute to technical direction and best practices for data science across Kikoff, not just Grant: how we do experimentation, how we use AI tooling, how we review each other's work. Minimum qualifications Experience partnering with product, engineering, and marketing peers across the whole arc of the work: strategy, goal setting, approach, and execution, not just the analysis at the end. A track record of defining metrics from scratch and getting a team to run on them. Designed and run experimentation programs, including changes where clean randomization wasn't available. Comfortable with quasi-experimental and causal inference methods, and clear about their limits. Hands-on with production-quality SQL and Python. You build pipelines, analyses, and models yourself. Experience building or working closely with models that drive decisions in a product, in any domain: ranking, fraud, forecasting, personalization, underwriting, detection. We care about the judgment, not the vertical. AI tools are a core part of your daily analytical work and you can show how they changed the speed and quality of what you ship. You drive decisions with data in front of executive audiences, including when the data doesn't support the plan. Preferred qualifications Consumer fintech experience, especially products that expand access for un- and under-banked customers. Built an experimentation or causal inference practice in an org that didn't have one. Have taken a model from proof of concept to production, or shipped test and challenger models that changed a product decision. Prior staff or tech-lead scope: set direction for other ICs and owned a domain's data strategy. 8+ years in data science or analytics. Strong senior candidates will be considered for a Senior Data Scientist version of this role. Base Range $265,000 — $306,000 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 .

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. The Role: We’re looking for a Senior Frontend Engineer to help shape the future of our flagship credit building product — the engine behind our mission to help millions of Americans build and strengthen their credit. This role sits at the heart of our business. You’ll work on initiatives that directly improve retention, engagement, and revenue , while also exploring and scoping challenging new opportunities to drive the next wave of impact. Every project you work on is built hand-in-hand with PMs, designers, and data scientists , ensuring that features are not just shipped, but move the needle in a meaningful, measurable way . And it helps bring our core tradeline product to the next level of impact. Requirements: B.A. / B.S. / M.S. or strong self-taught fundamentals in computer science 5+ years of industry experience, with demonstrated breadth and depth of product impact Hands-on experience with React in production Ability to analyze data and distill information for business purposes Effectiveness as demonstrated by problem-solving skills in areas outside your expertise Desire to form strong professional bonds with startup-forward coworkers Base Range $244,000 — $292,000 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 .

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 Kikoff exists to help millions of people build credit. That only works if they trust us with their financial data. This role owns the Data Security pillar at Kikoff: how data is classified, accessed, encrypted, moved, and audited across our entire stack. You will own and dictate the data security roadmap. You define the strategy, sequence the work, and drive it to done. Your work will be felt by every engineer at Kikoff and every customer we serve, and it will shape how we handle sensitive data as we scale. In This Role, You Will Own the Pillar Own the data security roadmap end to end: classification, access controls, encryption, tokenization, and data flow security across AWS, Snowflake, and our internal pipelines. Set the strategy for how humans, services, and AI agents access sensitive data. You decide what good looks like and build towards it. Drive least-privilege access at scale, including brokered access patterns for our data warehouse and production databases rather than standing credentials. Build & Secure Design and ship tokenization and field-level protection for our most sensitive data Build column-level and role-based access controls across Snowflake and RDS, with audit visibility into who touched what and why Secure data flows between cloud storage, pipelines, and application services so the secure path is the default path Define and enforce access controls for AI agents to guarantee least privilege permissions and proper audibility. Prove It Build audit logging and data access monitoring that holds up in front of auditors and regulators, not just dashboards Support data mapping and privacy engineering work for new markets and regulatory regimes (GLBA, LGPD, state privacy laws) Partner with Legal and Compliance on data handling requirements, and translate them into infrastructure, not policy docs Enable Engineering Give engineers paved roads for handling sensitive data: reusable patterns, clear guidance, fast answers Threat model new data flows before they ship, not after Qualifications 6+ years in security engineering with deep, hands-on data security experience: encryption, tokenization, access control design, key management Strong command of AWS security primitives (IAM, KMS, S3 security, VPC controls) Experience securing a modern data stack: Snowflake or a comparable warehouse, plus relational databases in production You've designed and shipped access control systems, not just configured them. Row/column-level security, ABAC/RBAC, access brokering Fluency in at least one language for automation (Python, Go, Ruby, or similar) Comfortable in a regulated environment Hands-on with infrastructure-as-code (Terraform or Pulumi) Bonus Points Experience securing data access for AI/LLM systems and agentic workloads Tokenization at scale in fintech or payments Audit logging and data access monitoring you built yourself, not bought Privacy engineering depth: data mapping, retention, deletion pipelines, cross-border transfer controls Consumer fintech or financial services background Base Range $268,000 — $321,000 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 .

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. Calling all new grad and junior software engineers who are looking for fast personal and career growth in consumer fintech. Skip the bureaucracy of a big company and work with a seasoned startup product and engineering team. We balance best practices from our experience in post-IPO companies with the familiar intuition that comes from pre-IPO zero-to-one work. Our mission is to create fair, effective, and simple financial pathways to help 100M Americans reach their financial goals. Investors include Lightspeed, Coatue and GGV. Founders are serial entrepreneurs who co-founded and served as C-suite executives at 3 FinTech unicorns. Our backend is written in Ruby on Rails on AWS, using lots of vanilla infrastructure. Our frontend and mobile apps are written in ReactJS on Vercel and Flutter. Strong internships and general open-source experience are necessary, but familiarity with our particular stack is preferred. Requirements: B.A. / B.S. / M.S. or strong self-taught fundamentals in computer science Expertise in Rails, cloud infrastructure, ReactJS, or Flutter 2+ years of industry experience or equivalent Passion for early stage products and startups Desire to form strong professional bonds with coworkers Base Range $165,000 — $165,000 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 .