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Senior Staff Machine Learning Engineer, (ML Underwriting)
Affirm
- United States
- United States
Über
Define and drive multi?year, multi?team technical strategy for machine learning across affirm, ensuring alignment with company?wide priorities and influencing 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. Proficiency in Python and ML frameworks, including PyTorch and XGBoost. Deep 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, including streaming or batch data ingestion, feature stores, training pipelines, model serving, and monitoring. Strong technical leadership: defining long?term strategy, guiding 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 that support effective collaboration across our global engineering organization. Equivalent practical experience or a bachelors degree in a related field. Pay Grade R
Equity Grade 15 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 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 an employee stock purchase plan enabling you to buy shares of affirm at a discount. We believe its 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. By clicking Submit Application, you acknowledge that you have read affirms 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. #LI Remote #J-18808-Ljbffr
Sprachkenntnisse
- English
Hinweis für Nutzer
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