ML Engineer Jobs at Affirm with Visa Sponsorship
ML Engineer jobs at Affirm involve building credit risk models, fraud detection systems, and real-time decisioning infrastructure across its buy-now-pay-later platform. The company has an established sponsorship track record for this function, supporting candidates through H-1B visa, OPT, and employment-based Green Card pathways.
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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
-
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).
-
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 ML Engineer Jobs at Affirm
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Engineer Jobs at Affirm.
Get Access To All JobsTips for Finding ML Engineer Jobs at Affirm
Align your ML work to credit risk
Affirm's ML teams focus heavily on underwriting models and default prediction. Frame your resume around supervised learning, feature engineering for financial signals, or real-time inference pipelines rather than general-purpose ML projects.
Target roles that match your OPT timeline
If you're on F-1 OPT, confirm whether a role falls under a STEM-designated SOC code before applying. Affirm's ML Engineering positions typically qualify, giving you up to 36 months of work authorization before an H-1B filing is needed.
Ask about LCA filing scope during offer negotiation
Affirm operates with distributed and hybrid teams. When you receive an offer, confirm the Labor Condition Application will list your actual work location. A mismatch between your LCA worksite and where you physically work can create compliance issues with DOL.
Prepare your specialty occupation documentation early
For H-1B approval, USCIS must find the role a specialty occupation requiring a relevant degree. Collect transcripts, degree equivalency evaluations if your credential is foreign, and any coursework records tying your background to financial ML or applied statistics before your employer initiates the petition.
Use Migrate Mate to find open ML Engineer roles at Affirm
Affirm's sponsorship-eligible ML positions don't always stay open long. Use Migrate Mate to filter active ML Engineer listings at Affirm by visa type, so you're applying to roles where sponsorship is already confirmed rather than guessing from a generic careers page.
Understand when PERM becomes part of your path
If Affirm moves you toward an EB-2 or EB-3 Green Card, DOL requires a PERM labor certification before the I-140 petition. That process involves recruitment documentation and prevailing wage determinations, and typically takes 12 to 18 months before USCIS even sees your petition.
Frequently Asked Questions
Does Affirm sponsor H-1B visas for ML Engineers?
Yes, Affirm sponsors H-1B visas for ML Engineers. The company has a consistent track record of filing H-1B petitions for technical roles, and ML Engineering positions typically qualify as specialty occupations under USCIS standards given their degree requirements in computer science, statistics, or a related quantitative field. Sponsorship is generally discussed during the offer stage.
Which visa types are commonly used for ML Engineer roles at Affirm?
ML Engineers at Affirm most commonly work on H-1B status, F-1 OPT (including STEM OPT extensions), or TN visas for Canadian and Mexican nationals in qualifying occupations. For longer-term pathways, Affirm supports employment-based Green Card sponsorship through EB-2 or EB-3 categories, which involve PERM labor certification filed with DOL followed by an I-140 petition with USCIS.
What qualifications and experience does Affirm expect for ML Engineer roles?
Affirm's ML Engineer roles typically require a bachelor's or master's degree in computer science, statistics, or a related field, along with hands-on experience building production ML systems. Familiarity with credit risk modeling, fraud detection, or real-time inference is a practical advantage. Experience with Python-based ML frameworks and large-scale data pipelines is consistently expected across job postings.
How do I apply for ML Engineer jobs at Affirm?
You can browse and apply for ML Engineer positions at Affirm that include visa sponsorship through Migrate Mate, which filters listings by role and visa type so you're not sifting through roles that don't support your situation. Once you identify a match, apply directly and be prepared to discuss your visa status and timeline early in the process, ideally before the final interview round.
How do I time my H-1B filing if I'm currently on OPT at Affirm?
If you're working at Affirm on F-1 OPT, your employer must submit your H-1B registration during the annual lottery window in March. If selected, the petition is filed for an October 1 start date. STEM OPT gives you up to 36 months of total OPT work authorization, which typically provides enough runway to clear one full H-1B lottery cycle without a gap in employment authorization.