Affirm is hiring: Senior Staff Machine Learning Engineer, (ML Underwriting) in M
Affirm, Madison, WI, United States
Senior Staff Machine Learning Engineer (ML Underwriting)
Join to apply at
Affirm .
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.
What You’ll Do
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.
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.
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.
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.
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.
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.
What We Look For
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.
Experience leading end‑to‑end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. Use of distributed frameworks such as Spark, Ray, or similar large‑scale data processing systems.
Proficient in Python and ML frameworks, including PyTorch and XGBoost. Experience with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
Strong understanding of representation learning and embedding‑based modeling. Deep expertise in neural network‑based sequence modeling, including architectures such as Transformers, recurrent, or attention‑based models, and multi‑task learning systems. Comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
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.
Strong technical leadership: defining long‑term strategy, guiding research direction, and aligning work across teams. Recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
Exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. Mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
Strong verbal and written communication skills supporting effective collaboration across our global engineering organization.
Position requires equivalent practical experience or a Bachelor’s degree in a related field.
Pay Grade – R
Equity Grade – 15
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. A limited number of roles remain office‑based due to the nature of their job responsibilities.
Benefits
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 - 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.
For U.S. positions that could be performed in Los Angeles or San Francisco, 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.
#J-18808-Ljbffr
Join to apply at
Affirm .
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.
What You’ll Do
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.
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.
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.
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.
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.
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.
What We Look For
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.
Experience leading end‑to‑end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment. Use of distributed frameworks such as Spark, Ray, or similar large‑scale data processing systems.
Proficient in Python and ML frameworks, including PyTorch and XGBoost. Experience with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.
Strong understanding of representation learning and embedding‑based modeling. Deep expertise in neural network‑based sequence modeling, including architectures such as Transformers, recurrent, or attention‑based models, and multi‑task learning systems. Comfortable designing and optimizing models that learn from sequential or temporal event data at scale.
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.
Strong technical leadership: defining long‑term strategy, guiding research direction, and aligning work across teams. Recognized as a trusted expert who can drive clarity and execution even in ambiguous problem spaces.
Exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives. Mentor senior engineers, foster technical excellence, and contribute to a culture of continuous learning.
Strong verbal and written communication skills supporting effective collaboration across our global engineering organization.
Position requires equivalent practical experience or a Bachelor’s degree in a related field.
Pay Grade – R
Equity Grade – 15
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. A limited number of roles remain office‑based due to the nature of their job responsibilities.
Benefits
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 - 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.
For U.S. positions that could be performed in Los Angeles or San Francisco, 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.
#J-18808-Ljbffr