Affirm
ML Manager, Software Engineering (Decisions and Pricing Engineering EU)
Job Summary
This role is for an Engineering Manager overseeing a team of Machine Learning Engineers focused on developing and deploying credit underwriting models. Responsibilities include collaborating with cross-functional teams, setting strategic priorities, and guiding the team in building large-scale, resilient systems. The ideal candidate has extensive experience in machine learning engineering, leadership, and scaling distributed systems, with a strong emphasis on delivering impactful business solutions. The position offers remote work within Spain along with comprehensive benefits and a focus on diversity and inclusion.
Required Skills
Benefits
Job Description
Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.
Decisions and Pricing's mission is to deliver the best credit decisions for Affirm consumers while maintaining positive unit economics and being the highest converting and most competitive payment solution for our merchant partners. We’re looking for an Engineering Manager to lead a team of skilled Machine Learning Engineers in advancing our underwriting models. The successful candidate will align team efforts with company objectives, focusing on developing and deploying high-quality, production-ready machine learning models. They will lead the team in creating innovative solutions that support our financial and business goals.
What You’ll Do
- Collaborate with Product managers, cross functional engineering teams, designers and analysts to define product roadmap and execute on plan to build practical technology capabilities needed to realize the vision. Drive clarity from ambiguity to aid faster decisions grounded on principles.
- Drive planning, resource allocations, trade-offs and prioritization conversations with business and technical stakeholders to define epics in Jira and manage the quality of deliverables all the way to production
- Collaborate with product and platform teams to set strategic priorities and roadmaps for machine learning projects that enhance our credit assessment capabilities.
- Participate in quarterly planning and work closely with peers and teams to remove impediments, articulate tradeoffs and garner resources
- Build the best team - Grow globally minded teams by attracting and hiring diverse talent and build a strong leadership bench. Provide tailored coaching, feedback and mentoring for Engineers and inspire a team of full stack engineers
- Hire, coach, and mentor employees to increase their impact through regular performance development and feedback conversations.
- Foster a respectful and supportive environment for all team members that effectively leverages the diversity of the team.
- On-Call Rotation - There would be an on-call rotation for this role as a requirement.
What We Look For
- Extensive experience (8+ years) in machine learning engineering, with at least 2 years in a management role.
- Expertise in developing machine learning models and systems at scale, from concept through to business impact.
- Proficiency in machine learning techniques, including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.
- Strong engineering skills in Python and SQL, with experience in large-scale distributed systems such as Spark or Ray.
- Passion for working with cross-functional teams including Product, Design, Analytics and Business teams.
- Expert at synthesizing complex business, product, and technical requirements to consistently produce high quality system designs and software.
- Track record of hiring, mentoring, coaching, and developing diverse engineering talent.
- Comfortability with ambiguity and self-awareness to understand and navigate the unknown
- Demonstrated experience in building and scaling platforms and distributed systems that require high availability, resilience and meeting stringent SLO objectives is required.
- Excellent written and verbal English communication skills.
- Experience with Fintech and Retail industries is a plus
Compensation & Benefits
Base Pay Grade - P
Equity Grade - Spain 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: € 101,000 - 131,000
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 leave
- 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
#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.
We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:
- 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.
By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
Interested in this job?
Applications are no longer being accepted for this job.
Affirm
With Affirm, you can pay over time at your favorite brands. No late fees or compounding interest—just a more responsible way to say yes to the things you love.
See more jobsSafe Remote Job Search Tips
Verify Employer Thoroughly
Research the company's identity thoroughly before applying. Check for a professional website with contacts, active social media, and LinkedIn profiles. Verify details across platforms and look for reviews on Glassdoor or Trustpilot to confirm legitimacy.
Never Pay to Get a Job
Legitimate employers never require payment for applications, training, background checks, or equipment. Always reject upfront payment requests or demands for bank details, even if they claim it's for purchasing necessary work gear on your behalf.
Safeguard Your Personal Information
Protect sensitive data like SSN, bank details, or ID copies. Share this only after accepting a formal, written job offer. Ensure it's submitted via a secure company system or portal, never through insecure channels like standard email attachments.
Scrutinize Communication & Interviews
Watch for communication red flags: poor grammar, generic emails (@gmail), vague details, or undue pressure. Be highly suspicious of interviews held only via text or chat apps; legitimate companies typically use video or phone calls.
Beware of Unrealistic Offers
If an offer's salary or benefits seem unrealistically high for the work involved, be cautious. Research standard pay for similar roles. Offers that appear 'too good to be true' are often scams designed to lure you into providing information or payment.
Insist on a Formal Contract
Always secure and review a formal, written job offer or employment contract before starting work or sharing final personal details. Ensure it clearly defines your role, compensation, key terms, and conditions to avoid misunderstandings or scams.