Machine Learning Engineer, Affirm
ML Fraud
$142-210k
Salary dependent on location. + An employee stock purchase plan
POS installment loans
Be an early applicant
POS installment loans
1001+ employees
Be an early applicant
$142-210k
Salary dependent on location. + An employee stock purchase plan
1001+ employees
Company mission
To deliver honest and transparent financial products that improve users' lives.
Role
Who you are
- If you're passionate about machine learning, thrive on challenges, and want to make a tangible difference in fintech, Affirm is your opportunity
- 2+ years of experience as a machine learning engineer or PhD in a relevant field
- Proficiency in machine learning with experience in areas such as gradient boosting, online learning, and deep learning. Domain knowledge in fraud risk is a plus
- Strong programming skills in Python
- Experience using large scale distributed systems like Spark and Ray
- Experience using machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch
- Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
- The ability to present technical concepts and results in an audience-appropriate way
- Persistence, patience and a strong sense of responsibility – we build the decision making that enables consumers and partners to place their trust in Affirm!
- This position requires either equivalent practical experience or a Bachelor’s degree in a related field
What the job involves
- Join Affirm’s ML Fraud team as a Machine Learning Engineer II and advance our capabilities in detecting and preventing online fraud. Leverage cutting-edge algorithms and proprietary data to outsmart fraudsters while ensuring seamless experiences for genuine customers
- Your work will directly impact Affirm's financial performance by developing sophisticated models for real time transaction decisions
- Collaborate with experts to tackle complex challenges, create innovative solutions for emerging fraud patterns, and advance our fraud detection capabilities
- Help us create honest financial products that improve lives while growing your career in a dynamic, impactful environment
- Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of fraud. These models will protect victims’ identities from being stolen, prevent Affirm from incurring financial loss, and increase the trust that consumers and partners have in the Affirm ecosystem
- Partner with the ML platform team to build fraud specific ML infrastructure
- Research ground breaking solutions and develop prototypes that drive the future of fraud decisioning at Affirm
- Implement and scale data pipelines, new features, and algorithms that are essential to our production models
- Collaborate with the engineering, fraud, and product teams to define requirements for new products
- Develop fraud models to maximize user conversion while minimizing fraud losses and data costs
Our take
Affirm offers point-of-sale loans to consumers, working with merchants like Shopify, KAYAK, and Walmart. Buy now, pay later transactions have grown in popularity in recent years, and this business is tapping into the market with a totally different approach to credit - by delivering the Affirm card, the first US debit card with the option to pay-over-time.
Boating over 15 million customers and 245,000+ merchants, the company offers flexible payback options, ranging from 3 to 36 months. The interest rates run between 0% and 30%, so, while they are not necessarily the cheapest option, Affirm prides itself on having no fees for late payments, no hidden charges, and total transparency about what people will pay before they take out a loan.
Affirm collects payments from the customers and pays the merchants directly, shouldering the risk itself. The company has boosted its market share, expanding its availability beyond the US to include most of Canada, and continues to launch new features and create new partnerships towards bettering its offering.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
-11% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Sep 2020
$500m
SERIES G
Apr 2019
$300m
SERIES F
Total funding: $1.1bn
Company benefits
- Spending wallets
- Supportive communities
- Remote-first workforce
- Generous time off
- Health benefits
- Mental healthcare
- Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
- We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
- We offer 24 company-wide paid days off—which help our teams collectively pause to recharge
- Learning & development
Company values
- People Come First
- No Fine Print
- It's On Us
- Simpler is Better
- Push the Envelope
Company HQ
Chinatown, San Francisco, CA
Articles
Leadership
Max Levchin
(CEO)Has founded/co-founded numerous companies, holding various executive positions at each, including Paypal, Slide, Glow, HVF Labs, and SciFi VC. Also worked at large brands including Google, Yelp, Yahoo, and Evernote.
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