Machine Learning Jobs at Affirm with Visa Sponsorship
Machine Learning jobs at Affirm involve work on credit risk modeling, fraud detection, and real-time decisioning infrastructure in a regulated fintech environment. The company has a consistent track record of sponsoring work visas for ML talent, supporting candidates from early-stage OPT through long-term employment-based immigration.
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Get Access To All JobsINTRODUCTION
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
On the Servicing ML team, you will build and improve machine learning and AI systems that automate customer operations such as disputes, returns, fraud, and chargebacks to make the best decisions for Affirm and our customers. You will work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring.
ROLE AND RESPONSIBILITIES
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You will develop AI systems that automate dispute and chargeback handling using structured evidence and business logic, creating a better experience for our customers.
-
You will build models that automate refunds, getting money back to our customers faster.
-
You will build and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows to produce structured, actionable outputs.
-
You will prototype new modeling ideas, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
-
You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.
BASIC QUALIFICATIONS
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You have a total of 2+ years of experience as a machine learning engineer.
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Strong Python skills and experience writing production-quality code.
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Experience building and evaluating models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost).
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Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including structured extraction, prompt engineering, and orchestration frameworks like LangChain or LangGraph.
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Familiarity with document and unstructured data processing (PDF/image extraction, text parsing, or similar).
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Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
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Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
-
You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
-
You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
-
Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
-
You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
-
This position requires either equivalent practical experience or a Bachelor's degree in a related field.
PREFERRED QUALIFICATIONS
Base Pay Grade - L
Equity Grade - 6
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $160,000 - $210,000
USA base pay range (all other U.S. states) per year: $142,000 - $192,000
WORK ARRANGEMENT
LI-Remote
Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
We're extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
-
Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents.
-
Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses.
-
Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge.
-
ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount.
We believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
INTRODUCTION
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
On the Servicing ML team, you will build and improve machine learning and AI systems that automate customer operations such as disputes, returns, fraud, and chargebacks to make the best decisions for Affirm and our customers. You will work closely with experienced ML engineers, platform partners, and cross-functional stakeholders to take models from idea to prototype to production, and to keep them healthy with strong measurement and monitoring.
ROLE AND RESPONSIBILITIES
-
You will develop AI systems that automate dispute and chargeback handling using structured evidence and business logic, creating a better experience for our customers.
-
You will build models that automate refunds, getting money back to our customers faster.
-
You will build and maintain evidence extraction pipelines that process unstructured data using LLM-powered workflows to produce structured, actionable outputs.
-
You will prototype new modeling ideas, run offline experiments, and drive the best-performing approaches into production with appropriate risk controls.
-
You will collaborate across Engineering, Servicing Operations, Product, and ML Platform to define requirements, evaluate tradeoffs, and communicate results clearly to both technical and non-technical audiences.
BASIC QUALIFICATIONS
-
You have a total of 2+ years of experience as a machine learning engineer.
-
Strong Python skills and experience writing production-quality code.
-
Experience building and evaluating models for tabular classification problems (preferably gradient-boosted decision trees like LightGBM/XGBoost/CatBoost).
-
Experience building applications with LLM APIs (e.g., OpenAI, Anthropic), including structured extraction, prompt engineering, and orchestration frameworks like LangChain or LangGraph.
-
Familiarity with document and unstructured data processing (PDF/image extraction, text parsing, or similar).
-
Experience with ML lifecycle tooling for training orchestration, experimentation, and model monitoring (e.g., Kubeflow, Airflow, MLflow, or equivalent internal platforms).
-
Proficient in using AI-powered developer tools (e.g., Claude Code, Cursor, or similar) to accelerate iteration, debugging, and code quality as part of day-to-day development workflows.
-
You have mastered taking a simple problem or business scenario into a solution that interacts with multiple software components, and executing on it by writing clear, easily understood, well tested and extensible code.
-
You are comfortable navigating a large code base, debugging others' code, and providing feedback to other engineers through code reviews.
-
Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
-
You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
-
This position requires either equivalent practical experience or a Bachelor's degree in a related field.
PREFERRED QUALIFICATIONS
Base Pay Grade - L
Equity Grade - 6
Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.
Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)
USA base pay range (CA, WA, NY, NJ, CT) per year: $160,000 - $210,000
USA base pay range (all other U.S. states) per year: $142,000 - $192,000
WORK ARRANGEMENT
LI-Remote
Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.
We're extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
-
Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents.
-
Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses.
-
Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge.
-
ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount.
We believe It's On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.
Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
See all Machine Learning Jobs at Affirm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Machine Learning Jobs at Affirm.
Get Access To All JobsTips for Finding Machine Learning Jobs at Affirm
Frame your ML experience around financial risk
Affirm's ML roles sit at the intersection of consumer credit and model governance. Highlighting experience with risk scoring, loss forecasting, or compliance-aware modeling signals fit with the regulatory constraints fintech ML teams actually work under.
Verify your OPT STEM extension eligibility early
F-1 holders in ML roles at Affirm typically qualify for the 24-month STEM OPT extension. Confirm your degree's CIP code qualifies with your DSO before your initial OPT expires, so your 60-day grace period doesn't create a gap in your authorization timeline.
Target roles that use production ML systems
Affirm sponsors most consistently for roles where ML is core to the product, not exploratory. Job postings referencing model deployment, feature pipelines, or real-time inference indicate the kind of specialized need that typically drives H-1B and employment-based green card filings.
Understand the H-1B cap and Affirm's filing window
H-1B registration opens in March for an October 1 start date. If you're not selected in the lottery, Affirm's ML roles in credit infrastructure may qualify for cap-exempt filings through affiliated research institutions. Confirm this pathway with your recruiter early in the process.
Prepare documentation that maps your degree to the role
USCIS requires a direct relationship between your field of study and the specialty occupation. For ML roles, a degree in computer science, statistics, or applied mathematics strengthens the petition. If your degree is adjacent, a credentials evaluation letter from a NACES-approved evaluator reduces RFE risk.
Search Affirm ML roles through Migrate Mate
Affirm lists ML openings across multiple teams with different sponsorship profiles. Use Migrate Mate to filter active roles by visa type so you can identify which positions align with your current status before reaching out to a recruiter.
Frequently Asked Questions
Does Affirm sponsor H-1B visas for Machine Learning roles?
Yes, Affirm sponsors H-1B visas for Machine Learning positions. ML roles in credit risk, fraud detection, and model infrastructure are core to Affirm's product, which means they represent the kind of specialized, degree-dependent need that supports H-1B petitions. If you're subject to the annual cap lottery, confirm timing with your recruiter since registration opens each March for an October start.
How do I apply for Machine Learning jobs at Affirm?
Apply through Affirm's careers page or browse current openings filtered by visa sponsorship type on Migrate Mate. ML roles at Affirm typically require a technical screen, a take-home or live coding assessment focused on ML fundamentals, and a system design round. Mentioning your visa status early in the recruiter call avoids surprises late in the process.
Which visa types does Affirm commonly use for Machine Learning hires?
Affirm sponsors H-1B, F-1 OPT, F-1 CPT, and TN visas for ML roles, and supports EB-2 and EB-3 green card filings for longer-term employment. F-1 holders in ML typically qualify for the 24-month STEM OPT extension given the degree requirements for these roles. TN visa sponsorship is available for Canadian and Mexican nationals in qualifying occupations.
What qualifications does Affirm expect for Machine Learning positions?
Affirm's ML roles generally require a bachelor's or master's degree in computer science, statistics, applied mathematics, or a closely related field. Practical experience with model training pipelines, feature engineering, and production deployment matters more than academic credentials alone. Roles in credit risk or fraud modeling also value familiarity with regulatory environments and explainability requirements common in consumer finance.
How do I time my application around my visa status at Affirm?
If you're on OPT, apply with enough runway to complete the interview process and allow Affirm time to file an H-1B petition or process a status change before your authorization expires. USCIS premium processing can reduce H-1B adjudication to 15 business days if timing is tight. Coordinate your start date with the recruiter explicitly so HR can build the filing timeline around your situation.