Affirm

3 months ago

Manager, Machine Learning Engineering (Fraud)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Lead a team of ML engineers focused on fraud detection models in a production environment. Define technical and modeling strategy, drive adoption of advanced techniques (representation learning, transformer-based models), and collaborate with Product, Fraud Analytics, Risk, and Platform teams to integrate high-quality models into decisioning systems. Foster a culture of technical excellence and ownership while advancing fraud prevention capabilities at Affirm.

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Set the technical and modeling strategy for fraud detection, aligning team efforts with key business outcomes such as fraud loss reduction, approval rates, and customer experience
•Lead a team of machine learning engineers to design, build, and iterate on high-impact fraud models across the full ML lifecycle, from experimentation to production
•Drive the evolution of modeling approaches, including the adoption of representation learning, transformer-based methods, and other advanced techniques for modeling complex behavioral data
•Partner cross-functionally with Product, Fraud Analytics, Risk, and Engineering to define solutions, evaluate trade-offs, and ensure models are effectively integrated into decisioning systems
•Develop talent by coaching engineers, providing feedback, and fostering a high-performing team culture grounded in technical excellence and ownership

Pay and Benefits

Salary: USD 178,000 - 228,000 annually

Perks:Health InsuranceEsppTime Off

Key Requirements

•Bachelor’s in a technical field with 8+ years of industry experience, including 3+ years managing engineers
•Experience with modern ML approaches, including representation learning, deep learning, or transformer-based models, as well as traditional methods such as gradient-boosted trees
•Proven ability to lead teams delivering end-to-end ML solutions in production environments, including experimentation, evaluation, and model iteration in production
•Strong engineering fundamentals and experience working with scalable systems and data pipelines
•Track record of effective cross-functional collaboration with product, analytics, and engineering partners

Experience:8+ yearsFraudMachine learningPayments

Education:Bachelor's

Skills:Machine learningLeadershipCommunicationProblem-solving

Languages:English

Tech Stack:Gradient boostingTransformerRepresentation learningDeep learningProductionData pipelines

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 months ago

Manager, Machine Learning Engineering (Fraud)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 26 minutes agoStatus: Live

Job Summary

Location: Canada

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Set the technical and modeling strategy for fraud detection, aligning team efforts with key business outcomes such as fraud loss reduction, approval rates, and customer experience
•Lead a team of machine learning engineers to design, build, and iterate on high-impact fraud models across the full ML lifecycle, from experimentation to production
•Drive the evolution of modeling approaches, including the adoption of representation learning, transformer-based methods, and other advanced techniques for modeling complex behavioral data
•Partner cross-functionally with Product, Fraud Analytics, Risk, and Engineering to define solutions, evaluate trade-offs, and ensure models are effectively integrated into decisioning systems
•Develop talent by coaching engineers, providing feedback, and fostering a high-performing team culture grounded in technical excellence and ownership

Pay and Benefits

Salary: USD 178,000 - 228,000 annually

Perks:Health InsuranceEsppTime Off

Key Requirements

•Bachelor’s in a technical field with 8+ years of industry experience, including 3+ years managing engineers
•Experience with modern ML approaches, including representation learning, deep learning, or transformer-based models, as well as traditional methods such as gradient-boosted trees
•Proven ability to lead teams delivering end-to-end ML solutions in production environments, including experimentation, evaluation, and model iteration in production
•Strong engineering fundamentals and experience working with scalable systems and data pipelines
•Track record of effective cross-functional collaboration with product, analytics, and engineering partners

Experience:8+ yearsFraudMachine learningPayments

Education:Bachelor's

Skills:Machine learningLeadershipCommunicationProblem-solving

Languages:English

Tech Stack:Gradient boostingTransformerRepresentation learningDeep learningProductionData pipelines

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