Machine Learning Engineering Manager (Fintech)

TL;DR

Machine Learning Engineering Manager (Fintech): Managing a team of ML engineers building post-origination credit lifecycle models with an accent on repayment behavior, collections prioritization, and loss mitigation. Focus on designing and scaling advanced ML solutions using tree-based models, transformers, and agentic ML to drive critical business capabilities.

Location: Remote (UK, Poland, or Spain)

Salary: £142,000 – £190,000 per year

Company

Affirm is a fintech company reinventing credit to provide honest, fee-free buy now pay later options for consumers.

What you will do

• Set the technical strategy for the ML group focusing on repayment, collections, recovery, and loss mitigation.
• Lead the design and implementation of advanced ML solutions that drive critical company capabilities.
• Partner with product management, design, analytics, and risk leaders to manage technical sustainability and trade-offs.
• Mentor and develop engineering talent through consistent feedback, guidance, and technical leadership.
• Act as a force-multiplier by defining and advocating for technical solutions and operational processes.

Requirements

• 8+ years of industry experience, including 3+ years managing engineers.
• Background in financial services (credit/lending) with hands-on experience in post-origination modeling.
• Proficiency in ML, including tree-based models, transformers, deep learning, and agentic ML.
• Strong engineering skills and the ability to provide hands-on technical leadership.
• Must be based in the UK, Poland, or Spain.
• Bachelor's degree in a technical field or equivalent practical experience.

Culture & Benefits

• 100% subsidized medical, dental, and vision coverage for employees and dependents.
• Generous flexible spending wallets for technology, food, lifestyle, and family forming expenses.
• Competitive vacation and holiday schedules to ensure rest and recharge.
• Employee Stock Purchase Plan (ESPP) to buy shares of Affirm at a discount.
• Remote-first culture with flexibility to work from anywhere within the country of employment.