Senior Staff Machine Learning Engineer, (ML Underwriting)

Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without hidden fees or compounding interest.

Senior Staff Machine Learning Engineer (ML Underwriting)

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, utilizing advanced machine learning techniques to ensure responsible and accessible financial products.

What You’ll Do

Define and drive a multi‑year, multi‑team technical strategy for machine learning across the organization, ensuring alignment with company‑wide priorities and influencing partner roadmaps.

Lead the design, implementation, and scaling of advanced ML systems, setting architectural direction for complex, cross‑functional initiatives and ensuring systems remain reliable, extensible, and prepared for increasingly sophisticated 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. A relevant Ph.D. can count for up to 2 years of experience.

Experience leading end‑to‑end ML system design, from data architecture and feature pipelines to model training, evaluation, and production deployment, using distributed frameworks such as Spark, Ray, or similar large‑scale data processing systems.

Proficiency in Python and ML frameworks, including PyTorch and XGBoost, and experience with ML tooling for training orchestration, experimentation, and model monitoring, such as Kubeflow, MLflow, or equivalent internal platforms.

Deep understanding of representation learning and embedding‑based modeling, and expertise in neural‑network‑based sequence modeling, including Transformers, recurrent, or attention‑based models, and multi‑task learning systems.

Hands‑on experience with large‑scale distributed ML infrastructure : 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 capable of driving clarity and execution in ambiguous problem spaces.

Exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives, and fostering a culture of continuous learning.

Strong verbal and written communication skills that support effective collaboration across a global engineering organization.

Practical experience or a Bachelor’s degree in a related field.

Pay Grade : Equity Grade :

Base Pay Range (CAN) :

$206,000 – $256,000 per year.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness, and tech spending, and benefits (including 100% subsidized medical coverage, dental, and vision for you and your dependents). Eligible employees may also receive equity rewards offered by Affirm Holdings, Inc., the parent company.

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, 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.

Affirm is proud to offer a remote‑first company culture. Most roles are remote, and you can work almost anywhere within the country of employment. Some roles may require occasional on‑site work in an assigned office.

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, we consider 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.

Seniority Level

Mid‑Senior level

Employment Type

Full‑time

Job Function

Engineering and Information Technology

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