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Senior Staff Machine Learning Engineer, (Machine Learning)Affirm • Richmond, Virginia, United States
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Senior Staff Machine Learning Engineer, (Machine Learning)

Affirm
  • US
    Richmond, Virginia, United States
  • US
    Richmond, Virginia, United States
Jetzt Bewerben

Über

Remote Canada
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 team as a Senior Staff Machine Learning Engineer and become a pivotal part of our innovative ML team. Our team is dedicated to affirming the mission of revolutionizing financial services with transparency and inclusivity at its core. We are utilizing advanced machine learning techniques to ensure responsible and accessible financial products.
What you’ll do
Define and drive multi-year, multi-team technical strategy for machine learning across the company, 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 reliability, extensibility, and scalability.
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.
Provide broad technical leadership across the ML organization, mentoring senior engineers, elevating design and code quality, and sharing expertise through documentation, talks, and cross-organizational guidance.
Drive clarity and alignment on ambiguous, high-stakes technical decisions, resolving cross-team tensions and balancing competing priorities.
Champion operational and system excellence, owning the long-term health, availability, and evolution of critical ML systems with robust testing, monitoring, and reliability practices.
What we look for
10+ years of experience in researching, designing, deploying, and operating large-scale, real-time machine learning systems with measurable business impact. Relevant PhD may count for up to 2 years of experience.
Experience leading end-to-end ML system design, including data architecture, feature pipelines, model training, evaluation, and production deployment using distributed frameworks such as Spark, Ray, or similar.
Proficiency in Python and ML frameworks, including PyTorch and XGBoost, and familiarity with training orchestration, experimentation, and model monitoring tools such as Kubeflow, MLflow, or equivalent internal platforms.
Strong understanding of representation learning and embedding-based modeling, with deep expertise in neural network-based sequence modeling (Transformers, recurrent, attention-based models) and multi-task learning systems.
Hands‑on experience with large-scale distributed ML infrastructure, such as streaming or batch ingestion, feature stores, training pipelines, model serving, inference, monitoring, and automated retraining.
Proven technical leadership: defining long-term strategy, driving research direction, and aligning work across teams.
Exceptional judgment, collaboration, and communication skills, enabling effective technical discussions with engineers, researchers, and executives.
Strong verbal and written communication skills to support collaboration across a global engineering organization.
Equivalently practical experience or a Bachelor’s degree in a related field.
Compensation and Benefits Pay Grade – R Equity Grade – 9
Base pay is part of a total compensation package that may include monthly stipends for health, wellness, and tech spending, and benefits such as 100% subsidized medical coverage, dental and vision for you and your dependents. Employees may also be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).
CAN base pay range per year: $206,000 – $256,000
Benefits include:
Health care coverage – affirm covers all premiums for all levels of coverage for you and your dependents
Flexible Spending Wallets – generous stipends for technology, food, various lifestyle needs, and family forming expenses
Time off – competitive vacation and holiday schedules allowing you to take time to rest and recharge
ESPP – An employee stock purchase plan enabling you to buy shares of affirm at a discount
Remote Work Affirm is a remote‑first company. The majority of our roles are remote, and you can work almost anywhere within Canada. Some roles may require occasional work from an assigned affirm office.
EEO Statement 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.
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  • Richmond, Virginia, United States

Sprachkenntnisse

  • English
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