Senior ML Engineer Jobs at Affirm with Visa Sponsorship
Affirm builds credit products on real-time machine learning, so Senior ML Engineer roles here sit at the intersection of financial risk modeling and production ML systems. Affirm has a consistent track record of sponsoring work visas for this function across multiple visa categories.
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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.
See all 33+ Senior ML Engineer at Affirm jobs
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Get Access To All JobsTips for Finding Senior ML Engineer Jobs at Affirm Jobs
Frame your ML work around financial risk
Affirm's ML systems power underwriting, fraud detection, and credit decisioning. Highlight experience with risk-sensitive models, not just general deep learning work. Projects involving imbalanced datasets, credit scoring, or real-time inference pipelines will resonate with their hiring teams.
Verify your OPT timing before applying
If you're on F-1 OPT, confirm your remaining authorization window covers Affirm's full interview and onboarding timeline. A role this senior typically takes eight to twelve weeks from first screen to offer. STEM OPT extension eligibility can protect you if timing is tight.
Target roles with LCA-backed wage levels
Affirm files Labor Condition Applications with DOL before sponsoring H-1B workers. Senior ML Engineer roles at a fintech of this scale are typically certified at wage level III or IV. Cross-reference open job listings against public LCA disclosure data to confirm the role's prevailing wage tier.
Prepare your degree equivalency documentation early
Affirm's H-1B petitions require demonstrating specialty occupation status. If your degree is from outside the U.S., get a credential evaluation completed before your offer stage. A three-year bachelor's degree in computer science or a related field can qualify with the right evaluation.
Ask about cap-exempt filing options at offer stage
If you already hold H-1B status with another employer, Affirm can file an H-1B transfer without waiting for the next lottery. Raise this during the offer conversation so their immigration counsel can initiate the I-129 petition promptly and avoid any gap in your work authorization.
Use Migrate Mate to track open Senior ML Engineer roles
Affirm posts Senior ML Engineer openings across multiple teams simultaneously. Use Migrate Mate to filter for Affirm roles by visa type so you're applying to positions where H-1B or Green Card sponsorship is already confirmed, not just listed as a possibility.
Senior ML Engineer at Affirm jobs are hiring across the US. Find yours.
Find Senior ML Engineer at Affirm JobsFrequently Asked Questions
Does Affirm sponsor H-1B visas for Senior ML Engineers?
Yes, Affirm sponsors H-1B visas for Senior ML Engineer roles. Affirm files Labor Condition Applications with DOL to establish prevailing wages and then petitions USCIS on the worker's behalf. If you're already in H-1B status elsewhere, Affirm can file a transfer petition outside the annual lottery, which significantly simplifies the process.
Which visa types does Affirm commonly use for Senior ML Engineer roles?
Affirm sponsors across several categories for Senior ML Engineers, including H-1B, F-1 OPT and CPT for candidates still completing or recently completing U.S. degrees, TN for Canadian and Mexican nationals in qualifying engineering roles, and employment-based Green Card pathways including EB-2 and EB-3 for longer-term sponsorship. The right category depends on your nationality, degree, and current immigration status.
What qualifications and experience does Affirm expect for Senior ML Engineers?
Affirm's Senior ML Engineer roles typically require hands-on experience building and shipping production ML systems, not just research or prototyping. Familiarity with real-time inference, model monitoring, and ML infrastructure is expected. Given Affirm's core business, exposure to credit risk models, fraud detection systems, or other financially regulated ML applications is a strong differentiator during the interview process.
How do I apply for Senior ML Engineer jobs at Affirm?
You can apply directly through Affirm's careers page or browse their open Senior ML Engineer roles filtered by visa sponsorship type on Migrate Mate. Affirm's interview process for this level typically includes a recruiter screen, a technical assessment focused on ML systems design, and several rounds with the engineering team. Preparing examples of end-to-end model deployment will strengthen your performance.
How do I time my application if my work authorization is expiring soon?
If you're approaching the end of F-1 OPT, apply early enough to allow for Affirm's full interview cycle plus USCIS processing time for an H-1B cap-gap or transfer. USCIS premium processing can reduce adjudication to around fifteen business days when timing is critical. Discuss your authorization end date openly with Affirm's recruiter so their immigration counsel can sequence the filing correctly.
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