Affirm
Senior Machine Learning Engineer (Underwriting)
Job Summary
Affirm is seeking a Machine Learning Engineer to develop scalable models that assess creditworthiness and support decision-making across the loan lifecycle. The role involves working with proprietary and third-party data to build and deploy models, collaborating with engineering and product teams, and scaling data pipelines. Candidates should have extensive experience in machine learning, proficiency in Python and SQL, and familiarity with distributed systems like Spark or Ray. The company offers competitive benefits, including health coverage, stock purchase plans, and flexible work arrangements.
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.
Join the Affirm team as a Machine Learning Engineer and contribute to the success of our ML Underwriting team. We are the driving force behind Affirm's core value proposition, leveraging cutting-edge machine learning to assess creditworthiness throughout the life cycle of loan applications. As a Machine Learning Engineer on our team, you will be at the forefront of developing high-quality, production-ready models that play a central role in our decision-making processes. Your contributions will be instrumental in shaping our financial landscape. If you have a strong interest in machine learning and enjoy challenging work, Affirm is the place for you!
What you'll do
-
Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of default and make an approval or decline decision to achieve business objectives
-
Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems
-
Research ground breaking solutions and develop prototypes that drive the future of credit decisioning at Affirm
-
Implement and scale data pipelines, new features, and algorithms that are essential to our production models
-
Collaborate with the engineering, credit, and product teams to define requirements for new products
What we look for
-
6+ years of experience as a machine learning engineer. Relevant PhD can count for up to 2 YOE
-
Experience developing machine learning models at scale from inception to business impact
-
Proficiency in machine learning with experience in areas such as Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.
-
Strong engineering skills in Python and data manipulation skills like SQL
-
Experience using large scale distributed systems like Spark or Ray
-
Experience using open source projects and software such as scikit-learn, pandas, NumPy, XGBoost, PyTorch, Kubeflow
-
Experience with Kubernetes, Docker, and Airflow is a plus
-
Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
-
Persistence, patience and a strong sense of responsibility – we build the decision making that enables consumers and partners to place their trust in Affirm
Pay Grade - N
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).
CAN base pay range per year: $150,000 - $200,000
#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.
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.