Affirm

Manager, Machine Learning Engineering, Checkout

Spain full-time Executive EUR103,000 - EUR139,000
full-time Executive level Technology & IT Salary listed Curated
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About the role

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

Join Affirm as a Machine Learning Engineering Manager and become a pivotal part of our International Credit Machine Learning group. Specifically, you will manage a team of ML engineers that builds the models powering credit lending decisions in countries across Europe and in Australia. You will lead your team in using novel ML techniques and rich data representations to predict repayment behavior and optimize how we offer loans to our borrowers.
In this role, you will help shape the future of machine learning at Affirm. You'll partner with engineering, product, and risk leaders to design, implement, and scale advanced ML solutions that drive critical capabilities across the company. You will mentor engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy.
What you'll do

Set the technical strategy for your team, and help your engineers tie it together with critical, business-impacting projects in our underwriting system

Act as a force multiplier through your definition and advocacy of technical solutions and operational processes.

Collaborate across teams in the product development lifecycle by partnering with product management, design, analytics, and risk to ensure technical sustainability, risks and trade-offs are well understood and managed.

Develop talent by providing feedback and guidance, and leading by example.

On-Call Rotation - There would be an on-call rotation for this role as a requirement.

What We Look For

Bachelor's in a technical field with 8+ years of industry experience, including 3+ years managing engineers.

A background in financial services, specifically in credit / lending.

Proficiency in machine learning with experience in areas including tree-based models, transformers, deep learning, and agentic ML.

Strong engineering skills and the ability to provide hands-on technical leadership while working with our code and architecture.

You thrive in ambiguity, and are comfortable moving from low-level language idioms all the way to the architecture of large systems to understand how they work

Compensation & Benefits

Base Pay Grade- P

Equity Grade- 6

Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.

Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).

ESP base pay range per year: €103,000 - €139,000

Additional benefits include:

Flexible Spending Wallets for tech, food and lifestyle

Away Days - wellness days to take off work and recharge

Learning & Development programs

Parental benefit

Employee Resource & Community Groups

We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role.

Location - Remote Spain

Remote-first with flexibility built inAffirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Benefits designed for youOur benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

Health coverage at no cost: We cover 100% of premiums for employees and their dependents.

Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.

Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.

Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Executive
Technology & IT Data Analysis Remote Collaboration Manager Machine Learning Executive level

Likely questions

  1. Tell us about work you have done that is close to the Manager, Machine Learning Engineering, Checkout role.
  2. How would you approach your first 30 days at Affirm?
  3. Which of Data Analysis, Remote Collaboration and Manager have you used recently, and what did it help you achieve?
  4. How have you led people, improved a process, or made a hard decision in a previous role?
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Data Analysis, Remote Collaboration and Manager.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Manager, Machine Learning Engineering, Checkout role because I can bring practical experience in Data Analysis, Remote Collaboration and Manager, learn the team quickly, and contribute to the outcomes Affirm needs from this hire.

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