ML Engineer Jobs at Affirm with Visa Sponsorship
Affirm hires ML Engineers to build 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, 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. Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to Affirm's mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques ensuring responsible and accessible financial products. In this role, you will help shape the future of machine learning at Affirm. You’ll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy. If you are passionate about modern machine learning and excited to drive high-impact innovation across a growing organization, Affirm is the place for you.
ROLE AND RESPONSIBILITIES
You will define and drive multi-year, multi-team technical strategy for machine learning across Affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms.
You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads.
You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods.
You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance.
You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.
BASIC QUALIFICATIONS
You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems.
You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
You have deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining.
You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.
This position requires equivalent practical experience or a Bachelor’s degree in a related field.
COMPENSATION
- Pay Grade - R
- Equity Grade - 15
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: $260,000 - $310,000
USA base pay range (all other U.S. states) per year: $232,000 - $282,000
LOCATION
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.
BENEFITS
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. Join the Affirm team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to Affirm's mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques ensuring responsible and accessible financial products. In this role, you will help shape the future of machine learning at Affirm. You’ll partner with ML Platform, engineering, product, and risk leaders to design, implement, and scale advanced modeling approaches that drive critical decisions across the company. You will elevate our modeling capabilities, influence architectural direction, and ensure our systems can support increasingly sophisticated workloads. You will mentor senior engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy. If you are passionate about modern machine learning and excited to drive high-impact innovation across a growing organization, Affirm is the place for you.
ROLE AND RESPONSIBILITIES
You will define and drive multi-year, multi-team technical strategy for machine learning across Affirm, ensuring alignment with company-wide priorities and influencing the roadmaps of partner teams and platforms.
You will lead the design, implementation, and scaling of advanced ML systems, setting the architectural direction for complex, cross-functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated modeling workloads.
You will partner deeply with ML Platform, product, engineering, and risk leadership to shape long-term modeling capabilities, define new opportunities for ML impact, and guide infrastructure evolution required for next-generation ML methods.
You will provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and spreading ML expertise through documentation, talks, and cross-org guidance.
You will drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions, balancing competing priorities, and exercising judgment optimized for the broader engineering organization.
You will champion operational and system excellence at the area level, owning the long-term health, availability, and evolution of critical ML systems, and ensuring robust testing, monitoring, and reliability practices across teams.
BASIC QUALIFICATIONS
You have 10+ years of experience researching, designing, deploying, and operating large-scale, real-time machine learning systems, with a proven record of driving technical innovation and delivering measurable business impact. Relevant PhD can count for up to 2 YOE.
You have experience leading end-to-end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. You use distributed frameworks such as Spark, Ray, or similar large-scale data processing systems.
You are proficient in Python and ML frameworks, including PyTorch and XGBoost. You are experienced with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
You have a strong understanding of representation learning and embedding-based modeling. You possess deep expertise in neural network-based sequence modeling, including architectures such as Transformers, recurrent, or attention-based models, and multi-task learning systems. You are comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
You have deep hands-on experience with large-scale distributed ML infrastructure, including streaming or batch data ingestion, feature stores, feature engineering, training pipelines, model serving and inference infrastructure, monitoring, and automated retraining.
You provide strong technical leadership: defining long-term strategy, guiding research direction, and aligning work across teams. You are recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
You demonstrate exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. You mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
You have strong verbal and written communication skills that support effective collaboration across our global engineering organization.
This position requires equivalent practical experience or a Bachelor’s degree in a related field.
COMPENSATION
- Pay Grade - R
- Equity Grade - 15
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: $260,000 - $310,000
USA base pay range (all other U.S. states) per year: $232,000 - $282,000
LOCATION
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.
BENEFITS
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.
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Get Access To All JobsTips for Finding ML Engineer Jobs at Affirm Jobs
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.
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.
ML Engineer at Affirm jobs are hiring across the US. Find yours.
Find ML Engineer at Affirm JobsFrequently 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.
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