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Staff Software Engineer, Machine Learning (Consumer ML)

Spain flag Spain


Posted 12 days ago

Job Type

Full Time


$84k - $126k




  • Affirm is revolutionizing credit to be more transparent and consumer-friendly, enabling buy now, pay later without hidden fees or interest.

  • The Staff Software Engineer will lead the development of ML-powered solutions for personalized user experiences, search optimization, and other customer-centric challenges.

  • Opportunities include working on cutting-edge ML algorithms, collaborating with diverse teams, and influencing the strategic implementation of machine learning across Affirm.


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.

The Consumer Platform ML team’s mission is to deliver state of the art ML algorithms that will help build robust and scalable customer products. We use a data-driven approach to solve the problems and deliver ML-powered smart user experiences on the consumer apps and website. This team works in close partnership with our product managers, application and website teams to deeply understand the problems and deliver the most impactful solutions. We are constantly faced with challenges at industrial scale such as Personalization, Information Retrieval, Relevance Ranking and are pushing the boundary of how Affirm thinks of its data.

We are looking for highly motivated engineers to help build this team in Spain. Come join us!

What you’ll do

  • Design, develop, and deploy a ML-powered solution for building effective personalized user experiences, search optimization and other challenging problems in customer space

  • Build tools for our team to enable (1) personalization of content (2) relevance ranking, and (3) better and more effective information retrieval

  • Partner with Analyst, Data Science, and Product engineering teams to build production machine learning models; your models will decide what, when and to who will be shown in our app and website

  • Develop our understanding of new data sources and how they may improve our existing processes

  • Work closely with Affirm’s mobile application, website application, marketing, and analytics teams to understand our performance modeling strategies and the business drivers underlying those strategies

  • Serve as a trusted advisor on the application and implementation of machine learning across Affirm

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

What we look for

  • B.S. with 8+ years of industry experience, M.S. with 7+ years, PhD with 6+ years, or equivalent experience

  • Demonstrated experience designing real time systems and writing production-quality software

  • Experience with the AWS technical stack and data infrastructure such as MySQL, Spark, Kubernetes, Docker, and Airflow

  • Proficiency in machine learning with experience in areas such as gradient boosting, deep learning, recommendation systems, computational advertising, reinforcement learning, financial forecasting, time series analysis, anomaly detection, monte-carlo simulations, and Markov decision processes

  • Strong programming skills in Python. Experience using frameworks for machine learning and data science like scikit-learn, pandas, numpy, XGBoost, TensorFlow, mllib

  • Excellent written and oral communication skills including the capability to drive requirements with product and engineering teams and present technical concepts and results in an audience-appropriate way

  • Ability to work efficiently both solo and as part of a team; willingness to learn new things and mentor others

  • Passion to change consumer banking for the better, while developing a deeper understanding of applied machine learning

Compensation & Benefits

Pay Grade - ESP31

Employees new to Affirm or promoted into a new role, typically begin in the min to mid range.

ESP base pay range per year:

Min: €83,900

Mid: €104,800

Max: €125,800

We offer a competitive package, with some highlights listed below.

  • Flexible Spending Wallets for tech, food and lifestyle

  • Generous time off policies

  • Away Days - wellness days to take off work and recharge

  • Learning & Development programs

  • Parental leave

  • Robust health benefits

  • 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


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 the for applicants within the United States, the for applicants applying from Poland, the for applicants applying from Spain, or the for applicants applying from the United Kingdom, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.


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