In emerging markets, credit infrastructure is broken. Lenders rely on messy documents, fragmented borrower communication, and manual review
Kita is the AI platform for global lending operations. We automate loan origination, application completion, document verification, and credit review for lenders in markets where underwriting is still trapped in messy documents and manual follow-up — from the Philippines and Mexico to the US. Kita’s AI credit officer works directly with borrowers over WhatsApp, Viber, SMS, and email to collect missing information, resolve inconsistencies, and keep applications moving, while our AI underwriter extracts fraud-checked data and localized risk signals from chaotic financial documents to support faster, higher-quality credit decisions. The result is a more complete application pipeline, dramatically lower manual review burden, and a lending operation that moves faster without compromising risk control.
We’re a Stanford AI team backed by Y Combinator, top funds, and leading angels across Silicon Valley and Southeast Asia. During the YC batch, we grew ~40% week-over-week with customers across three continents. Our CTO was ranked #1 in Stanford CS in 2025.
Kita is looking for an exceptional Applied ML Intern to work directly with the founding team on some of the hardest problems in lending, fraud detection, and document intelligence.
We want someone highly technical, extremely fast, and excited to take on complex financial, credit, ML problems — from model prototyping and evaluation to data pipelines, backtesting, vision systems, and production-facing experiments.
You’ll work across machine learning, data science, computer vision, and product engineering to help build the intelligence layer behind Kita’s products. That includes figuring out which signals in messy financial documents actually predict repayment and fraud, designing evaluation systems for high-stakes underwriting workflows, and helping turn raw models into systems that customers can trust.
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What you’ll work on
Strong candidates will likely have:
Especially exciting backgrounds include:
In emerging markets, open finance is still nascent. Most of the population is traditionally unbanked, banking APIs don’t exist, and a borrower’s financial history lives in documents: e-wallet records, bank statements, utility bills, and more. Because this data is unstructured, credit and risk teams are forced into manual review. This slows decisioning, increases costs, and caps lending volume.
Kita is the AI platform for global lending operations. We help lenders in emerging markets automate application completion, document verification, and underwriting from messy financial documents — using AI to extract fraud-checked data and localized risk signals that power faster, better credit decisions.
Under the hood, Kita is a learning engine. We link document-level signals to repayment outcomes, allowing our models to continuously improve fraud detection and risk assessment over time. This creates a compounding advantage for lenders as their distinct underwriting decisions feed back into the system.
We’re Carmel and Rhea. We met before Stanford and have been building together ever since. Carmel is from Manila, is a repeat founder, and spent three years in product at Apple. Rhea has a research background in computer vision and received the highest honor in Stanford Computer Science. Together, we combine deep local context with strong technical execution to build the infrastructure that expands access to credit in emerging markets.
Salary
$5,000 - $8
Location
San Francisco, CA, US
