---
title: 'Machine Learning Engineer, Link at Stripe'
canonical: 'https://feeny.ai/job/machine-learning-engineer-link-stripe-new-york-6m7m881e9s5p'
type: 'job'
last_seen: '2026-10-18'
---

# Machine Learning Engineer, Link at Stripe

- **Company:** Stripe
- **Location:** New York, NY
- **Posted:** 2026-09-21
- **Last confirmed live:** 2026-10-18
- **Apply:** https://stripe.com/jobs/search?gh_jid=8197886

## Job description

## Who we are

## About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

## About the team

Link is a digital wallet designed for fast and secure online payments. It allows consumers to save and use their preferred payment methods across the Link network, helping them check out quickly and securely wherever Link is accepted.

The Link Fraud and Auth team works to make Link the most trusted and highest-performing way to pay. We protect consumers and merchants from fraud, abuse, and financial loss while maximizing authorization rates for good users. Our work spans consumer-facing experiences, payment infrastructure, and ML powered risk systems.

We manage fraud and financial risk across a growing range of novel Link features, including Link’s agentic wallet, stored balance, and LPMs. The team also owns Instant Bank Payments, a proprietary payment method built on ACH rails, offering merchants immediate confirmation while protecting them from bank-initiated returns. IBP is the heart of Link’s revenue engine, giving LFA engineers the opportunity to shape and scale one of Link’s most important products.

## What you’ll do

As a machine learning engineer on Link Fraud and Auth, you’ll build and operate models and risk decisioning systems that protect Link while helping more legitimate payments succeed. You’ll work across the full machine learning lifecycle, from analyzing fraud patterns and identifying opportunities to building, deploying, monitoring, and improving models in production. You’ll use data to form hypotheses, make practical modeling choices, and define technical direction in partnership with Engineering, Product, and Data Science. Your work will directly influence Link’s fraud performance, authorization rates, and ability to expand into new products and payment experiences.

## Responsibilities

- Build, train, evaluate, deploy, and own machine learning models that detect fraud and abuse across Link.
- Use large-scale datasets to investigate emerging threats, develop hypotheses, and identify opportunities to improve payment performance.
- Develop pragmatic machine learning solutions, including tree-based models and other approaches suited to real-time risk decisioning.
- Design data pipelines, features, evaluation methods, experiments, and monitoring systems that support reliable production models.
- Build and improve risk decisioning systems that integrate with other parts of Stripe’s payments stack.
- Own ambiguous problems from initial analysis and problem definition through technical design, implementation, launch, measurement, and iteration.
- Collaborate with Engineering, Product, Data Science, and Risk partners across Stripe to turn model improvements into durable product outcomes.

## Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

## Minimum requirements

- 6+ years of industry experience building and shipping machine learning models in production.
- Strong programming skills in Python and experience with common data and machine learning tools, such as SQL, Spark, and XGBoost.
- Strong knowledge of production machine learning systems, including data pipelines, feature development, model evaluation, deployment, monitoring, and iteration.
- Experience working with large and complex datasets and applying data analysis, statistics, and experimentation fundamentals.
- Demonstrated ability to take an open-ended business problem, determine where machine learning can help, and own the solution through production.
- Strong judgment in selecting practical modeling approaches and evaluating tradeoffs among model performance, system complexity, latency, and business impact.
- Strong collaboration skills and the ability to work across teams and contribute to peers' success.

## Preferred qualifications

- Experience applying machine learning to fraud detection, risk modeling, payment authorization, identity, account security, or another adversarial domain.
- Experience building real-time, low-latency machine learning or risk decisioning systems at scale.
- Experience integrating models into production services and designing reliable systems around model outputs.
- Experience with payments, fintech, digital wallets, or money movement.
- Strong software engineering skills and experience designing solutions across the machine learning and product stack.

## About Stripe

## Core Business
- Primary industry: Financial services / payments infrastructure
- Target customers: B2B – from startups to global enterprises (e.g., Le Monde, trucking companies)
- Mission: “Increase the GDP of the internet” by making online commerce easier and more accessible

## Products & Services
- **Stripe Payments**: Accept and optimise payments globally – online and in person; supports 135+ currencies and payment methods [stripe.com](https://stripe.com/)
- **Stripe Billing**: Manage subscriptions, invoices, and recurring revenue; over 200 million active subscriptions managed [stripe.com](https://stripe.com/)
- **Stripe Connect**: Embed payments into platforms and marketplaces
- **Stripe Atlas**: Incorporate a company, get everything needed to fundraise and start selling
- **Stripe Terminal**: In-person payments with customisable card readers
- **Stripe Issuing**: Create and manage a card issuing programme
- **Stripe Climate**: Automatically contribute a fraction of revenue to carbon removal

## Market Standing
- **Valuation/Market Cap**: Not publicly available (private company)
- **Key Metric**: $1.9 trillion in payments volume processed in 2025 [stripe.com](https://stripe.com/)
- **Notable Investors/Partners**: Not disclosed in provided sources
- **Growth Signals**:
  - Infrastructure underpins more than 1% of global GDP [stripe.com](https://stripe.com/jobs/life-at-stripe)
  - Over 8,000 employees across 25+ offices worldwide [stripe.com](https://stripe.com/jobs)
  - 99.999% historical uptime for Stripe services [stripe.com](https://stripe.com/)
  - Deploys 10,000+ times per day while maintaining five 9s of reliability [stripe.com](https://stripe.com/jobs/life-at-stripe)
  - 135+ currencies and payment methods supported [stripe.com](https://stripe.com/)

## Competitive Advantages
- **Scale & Reliability**: Processes massive transaction volumes with 99.999% uptime – a level of trust few competitors match.
- **Developer‑First Experience**: Obsessive focus on API design, documentation, and ease of integration; “start with a blank screen, work until a product is ready, polish until exceptional” [stripe.com](https://stripe.com/jobs/life-at-stripe).
- **Global Reach**: Supports 135+ currencies and payment methods, with local offices in 25+ cities to serve regional needs.
- **Network Effects**: The more businesses use Stripe, the more data and infrastructure advantages accrue, making it harder to switch.

## Strategic Focus
- **AI & Agentic Commerce**: Building economic infrastructure for AI, including monetisation through agentic commerce [stripe.com](https://stripe.com/).
- **Crypto & Stablecoins**: Enabling borderless money movement with stablecoins and crypto [stripe.com](https://stripe.com/).
- **Platform Expansion**: Continuing to add financial tools (billing, issuing, terminal, climate) that work individually or together.
- **Globalisation**: Deepening presence in markets like Japan, India, and Latin America.

## Why Work Here
- **Culture**: “Intense and kind” – high expectations paired with a supportive, transparent environment. Weekly all‑hands with senior leaders; decisions based on idea quality, not seniority [stripe.com](https://stripe.com/jobs/life-at-stripe).
- **Growth & Ownership**: “Promotions are tied to demonstrated impact, not tenure.” Employees get substantial responsibility early, often working outside their domain [stripe.com](https://stripe.com/jobs).
- **Work Model**: Hybrid/remote‑friendly – two main HQs (San Francisco & Dublin) plus 25+ offices, and many Stripes work from home or coworking spaces [stripe.com](https://stripe.com/jobs).
- **Benefits**: Comprehensive medical, mental health, financial advisory, family planning, and parental leave. Education team provides onboarding and ongoing expert‑led courses [stripe.com](https://stripe.com/en-gi/jobs/benefits).
- **Diversity & Inclusion**: Employee‑created resource groups (Stripe Communities), accommodations for disabilities, and a commitment to equal opportunity [stripe.com](https://stripe.com/jobs).

## Sources
1. [stripe.com/jobs/life-at-stripe](https://stripe.com/jobs/life-at-stripe)
2. [stripe.com/jobs](https://stripe.com/jobs)
3. [stripe.com/](https://stripe.com/)
4. [stripe.com/jobs/search](https://stripe.com/jobs/search)
5. [stripe.com/en-gi/jobs/benefits](https://stripe.com/en-gi/jobs/benefits)

## Other roles at Stripe

- [Project Manager, Total Rewards](https://feeny.ai/job/project-manager-total-rewards-stripe-chicago-nv7gy762wmgf) — Chicago, IL / Atlanta, GA
- [Indirect Tax Advisory Consultant](https://feeny.ai/job/indirect-tax-advisory-consultant-stripe-seattle-p1zmp05cqdsv) — Seattle, WA / San Francisco, CA / New York, NY
- [Solutions Engineer, AI Build Team](https://feeny.ai/job/solutions-engineer-ai-build-team-stripe-us-sf-us-nyc-wp7pbr4ke7wy) — Us-Sf Us-Nyc, United States
- [Account Executive, Product - Link: Bank Payments & Open Banking](https://feeny.ai/job/account-executive-product-link-bank-payments-open-banking-stripe-san-francisco-af52nwnz7sg0) — San Francisco, CA / Seattle, WA / Chicago, IL / New York, NY
- [Account Executive, Funded Startups DACH](https://feeny.ai/job/account-executive-funded-startups-dach-stripe-berlin-bq8ccw8cxwqk) — Berlin, Germany
- [Account Executive - Startup SaaS Platforms, Scaled UK Hunter](https://feeny.ai/job/account-executive-startup-saas-platforms-scaled-uk-hunter-stripe-dublin-4ke7stdt93ax) — Dublin, Ireland
- [Account Executive, Enterprise Grower (Benelux)](https://feeny.ai/job/account-executive-enterprise-grower-benelux-stripe-amsterdam-4mawh6x6791k) — Amsterdam, Netherlands
- [Team Lead, Managed Support](https://feeny.ai/job/team-lead-managed-support-stripe-mexico-city-8jg991gzagwk) — Mexico City, Mexico
- [Account Executive, SMB Commercial, Grower](https://feeny.ai/job/account-executive-smb-commercial-grower-stripe-dublin-74jj6eqd9ryn) — Dublin, Ireland
- [Partner Development Manager](https://feeny.ai/job/partner-development-manager-stripe-london-fxqqpmqr20dq) — London, United Kingdom