Affirm

3 days ago

Engineering Manager, Machine Learning Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Lead Affirm’s ML Training & Serving platform team, partnering with senior ICs to define and execute the roadmap across model training, deployment workflows, GPU infrastructure, and low-latency serving. You’ll manage and coach platform engineers while staying hands-on in technical decisions. Own infrastructure delivery and operational health, evaluate new ML infrastructure capabilities, and collaborate cross-functionally to ensure the platform supports Affirm’s top ML initiatives.

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Define and execute the roadmap for ML training and serving across training, deployment workflows, GPU infrastructure, and low-latency model serving.
•Lead, coach, and grow a team of platform engineers while staying 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 needs evolve, including transformer-based workloads and GPU compute.
•Collaborate with ML modeling, product, and infrastructure teams to support top ML initiatives and recruit, develop, and retain platform engineers.

Pay and Benefits

Salary: USD 181,000 - 241,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionTime OffEquity

Key Requirements

•7+ years of software and/or machine learning engineering experience, including 2+ years managing engineers and hands-on software engineering experience.
•Strong experience building and operating production ML or distributed systems infrastructure, with hands-on experience in 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.
•Bachelor’s degree in a technical field or equivalent practical experience.

Experience:7+ yearsMachine learningDistributed systemsDeep learning

Education:Bachelor's

Skills:People leadershipSystems thinkingTechnical judgmentCross-functional collaborationLeading through ambiguity

Languages:English

Tech Stack:GPUTransformer architecturesDeep learningML trainingML servingDistributed systems

Company Brief

Affirm

Provides point-of-sale lending and buy-now-pay-later (BNPL) solutions for consumers and merchants, enabling installment payments, consumer financing, and embedded financial services through APIs and partnerships with retailers and platforms.

Industry: Lending

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2012

Website LinkedIn

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Affirm

3 days ago

Engineering Manager, Machine Learning Platform

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Define and execute the roadmap for ML training and serving across training, deployment workflows, GPU infrastructure, and low-latency model serving.
•Lead, coach, and grow a team of platform engineers while staying 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 needs evolve, including transformer-based workloads and GPU compute.
•Collaborate with ML modeling, product, and infrastructure teams to support top ML initiatives and recruit, develop, and retain platform engineers.

Pay and Benefits

Salary: USD 181,000 - 241,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionTime OffEquity

Key Requirements

•7+ years of software and/or machine learning engineering experience, including 2+ years managing engineers and hands-on software engineering experience.
•Strong experience building and operating production ML or distributed systems infrastructure, with hands-on experience in 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.
•Bachelor’s degree in a technical field or equivalent practical experience.

Experience:7+ yearsMachine learningDistributed systemsDeep learning

Education:Bachelor's

Skills:People leadershipSystems thinkingTechnical judgmentCross-functional collaborationLeading through ambiguity

Languages:English

Tech Stack:GPUTransformer architecturesDeep learningML trainingML servingDistributed systems

Company Brief

Affirm

Industry: Lending

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 2012

Website LinkedIn