Data Science Engineer Jobs at Affirm with Visa Sponsorship
Affirm builds financial products that run on machine learning at their core, and Data Science Engineers sit at the center of that work. Affirm has a consistent track record of sponsoring international talent for this function, supporting candidates through the full visa process from initial offer through long-term work authorization.
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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.

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 Data Science Engineer Jobs at Affirm Jobs
Align your portfolio to credit risk modeling
Affirm's Data Science Engineering work centers on underwriting, fraud detection, and credit decisioning. Before applying, build portfolio projects that demonstrate experience with tabular financial data, model calibration, or risk scoring. Generic ML projects won't differentiate you in fintech hiring.
Verify your OPT start date timing
If you're on F-1 OPT, your employment start date must fall within your authorized period. Affirm's offer and onboarding timelines can run four to six weeks, so confirm your OPT expiration before signing. If it's close, discuss STEM OPT extension eligibility with your DSO immediately.
Understand how PERM timing affects your trajectory
Affirm sponsors EB-2 and EB-3 Green Cards, but PERM labor certification requires you to be in a stable role first. Ask during the offer stage whether your specific Data Science Engineer position has a defined sponsorship timeline, since teams and roles vary internally.
Prepare for technical screens grounded in production systems
Affirm's interview process for Data Science Engineers tests applied ML in production, not just algorithms. Review topics like feature engineering at scale, A/B testing for financial products, and model monitoring. Being strong on LeetCode alone won't clear the loop.
Negotiate visa filing timing during offer discussions
H-1B cap-subject filings only open in April for an October 1 start. If you receive an offer outside that window, clarify with the recruiter whether Affirm will bridge your status through OPT, TN, or another authorized classification while your petition is pending with USCIS.
Use Migrate Mate to surface active Data Science Engineer openings
Affirm posts roles across multiple channels, and not all listings clearly signal sponsorship eligibility. Use Migrate Mate to filter specifically for Affirm's Data Science Engineer roles that have a confirmed sponsorship track record, so you're applying where your visa situation is already understood.
Data Science Engineer at Affirm jobs are hiring across the US. Find yours.
Find Data Science Engineer at Affirm JobsFrequently Asked Questions
Does Affirm sponsor H-1B visas for Data Science Engineers?
Yes, Affirm sponsors H-1B visas for Data Science Engineers. The company has a consistent history of filing H-1B petitions for technical roles, and Data Science Engineering falls squarely within that pattern. If you're cap-subject, filings happen in April for an October 1 start date. If you're already in H-1B status with another employer, Affirm can file an H-1B transfer, which lets you start work as soon as USCIS receives the petition.
How do I apply for Data Science Engineer jobs at Affirm?
Apply through Affirm's careers page or find verified openings on Migrate Mate, which filters specifically for roles where international sponsorship is supported. Affirm's Data Science Engineer hiring process typically involves a recruiter screen, a technical assessment focused on applied ML and data systems, and a multi-round interview covering both coding and system design. Tailoring your materials to fintech use cases, particularly credit and fraud, strengthens your application.
Which visa types does Affirm commonly use for Data Science Engineer roles?
Affirm supports H-1B, F-1 OPT, F-1 CPT, TN, and employment-based Green Card sponsorship (EB-2 and EB-3) for Data Science Engineer roles. TN is available to Canadian and Mexican nationals in qualifying occupations. F-1 CPT is typically used for internships or co-op positions. For full-time roles, H-1B is the most common nonimmigrant path, with Green Card sponsorship available to employees who progress through the PERM process after establishing tenure.
What qualifications does Affirm expect for Data Science Engineer roles?
Affirm generally looks for a bachelor's or master's degree in Computer Science, Statistics, Applied Mathematics, or a closely related field. Beyond credentials, the role demands hands-on experience with ML model development and deployment in production environments. Familiarity with financial data, experimentation frameworks, and large-scale data pipelines is consistently valued across job descriptions. Candidates with Python fluency and experience working cross-functionally with product and engineering teams are competitive.
How do I time my application if my OPT or visa status is expiring soon?
Start the process early. Affirm's offer-to-start timeline can run several weeks, and USCIS processing for H-1B transfers or new petitions adds additional time. If you're on STEM OPT, confirm your expiration date and whether you've filed the extension before signing an offer. If your status is expiring within 60 days, raise this directly with the recruiter so the team can coordinate filing timelines and explore interim authorization options.
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