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Engineering Manager, Machine Learning Platform

Архив
Affirm · Финтех BNPL
Вакансия в архиве · закрыта 15.08
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Все вакансии: Engineering-менеджмент

О вакансии

Откуда можно работать
Удалённо из любой страны
Английский
C1
по другим вакансиям компании
Деньги
$230–290 тыс/год
указана работодателем в долларах
Даты
Опубликована 27.07 · видели у компании с 11.08 по 15.08 · закрыта 15.08
вакансия закрыта, проверки прекращены
Почему в каталоге:Основана выходцами из Восточной Европы, Кавказа и Центральной АзииПодробнее о компании →

Суть роли

We are seeking an Engineering Manager to lead our ML Training & Serving team. You will directly lead a team of platform engineers and combine effective people leadership with strong technical judgment in ML infrastructure. Working closely with senior ICs and partners across Machine Learning and Infrastructure, you will help shape the team’s roadmap, drive execution, and ensure the platform reliably supports Affirm’s ML priorities.

Что предстоит делать

  • Partner with senior ICs and engineering leadership to define and execute the roadmap for ML training & serving, spanning model training, deployment workflows, GPU infrastructure, and low-latency model serving.
  • Lead, coach, and grow a team of platform engineers while staying closely engaged in technical decisions and execution.
  • Drive delivery and operational health for the team’s infrastructure, balancing reliability, developer experience, performance, and cost.
  • Evaluate and adopt modern ML infrastructure capabilities as Affirm’s needs evolve, including transformer-based workloads and GPU compute.
  • Collaborate with ML modeling, product, and infrastructure teams to ensure the platform supports Affirm’s highest-priority ML initiatives.
  • Recruit, develop, and retain high-performing platform engineers.

Требования

  • 7+ years of industry experience in software and/or machine learning engineering, including 2+ years managing engineers and meaningful hands-on software engineering experience.
  • Strong experience building and operating production ML or distributed systems infrastructure, with hands-on experience in at least one of model training, model serving, deployment workflows, or GPU infrastructure.
  • Solid understanding of ML data needs, including training datasets, data quality, reproducibility, and evaluation data.
  • Familiarity with modern ML workloads, such as deep learning, transformer architectures, and large-scale training or serving.
  • Strong systems thinking and the ability to partner with senior ICs on architectural trade-offs.
  • Track record of delivering platforms or infrastructure that improve the productivity and impact of engineering or ML teams.
  • Experience recruiting, coaching, and developing engineers across career stages.
  • Effective cross-functional collaboration and the ability to lead through ambiguity.
  • Experience with applied ML modeling is a plus.
  • Bachelor’s degree in a technical field or equivalent practical experience.

Будет плюсом

  • Experience with applied ML modeling is a plus.

Условия и бенефиты

#LI-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.

  • 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.

[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.

Навыки

ML trainingML servingGPU infrastructuredistributed systemsDeep Learningtransformer architecturesmodel deployment workflowsteam leadershiprecruitingcross-functional collaboration

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