Senior Machine Learning Engineer, Affirm
$169-240k
POS installment loans
Open for applications
POS installment loans
1001+ employees
Open for applications
$169-240k
1001+ employees
Company mission
To deliver honest and transparent financial products that improve users' lives.
Role
Who you are
- 6+ years of experience as a machine learning engineer. Relevant PhD can count for up to 2 YOE
- This position requires either equivalent practical experience or a Bachelor’s degree in a related field
- 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. Domain knowledge in credit risk is a plus
- 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
What the job involves
- Join the Affirm team as a Senior Machine Learning Engineer and contribute to the success of our Machine Learning Underwriting team
- We are the driving force behind Affirm's core value proposition, leveraging cutting-edge machine learning to assess risk and make decisions throughout the life cycle of loan applications
- As a Senior 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 real-time 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!
- 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
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.
Boasting over 21M consumers and 337,000+ 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
-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
- Compensation: We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
- Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
- Supportive Communities: Get involved with our employee resource groups and community groups
- Remote-first Workforce: If your role is remote, you can set up shop anywhere in your home country
- Generous Time Off: Take the time you need when life happens
- Health Benefits: Get a plan that fits your needs
- Mental Healthcare: Take care of your mind with great mental health programs
- Parental Leave: Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
- Away Days: We offer 20 company-wide paid days off—which help our teams collectively pause to recharge
- Learning & Development: Engage in exciting learning programs to level up your growth
Company HQ
Chinatown, San Francisco, CA
Leadership
Max Levchin
(Co-Founder & 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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