Level

Affirm

Machine Learning Engineer II (ROA + LTV ML)

Affirm is hiring a Machine Learning Engineer II (ROA + LTV ML) for a remote role open to applicants in Canada. It pays $133k-$183k a year and Level rates it ; you can apply on Level.

Level's read on this job

  • On Level's scale, this machine learning engineer role is Builds AI ●●●●: the job is building AI systems.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include scikit-learn, XGBoost and Python.
  • Level lists 213 other open roles at Affirm.
  • The role was posted in the last few days.

AI in this role

Develop production-ready machine learning models for credit decisioning, default prediction, and risk assessment at scale.

scikit-learnxgboostpythonsqlsparkraypandasnumpykubeflow
machine-learningcredit-riskdeep-learningdistributed-systems

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most.

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

  • 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 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, Kubeflow

  • Experience developing machine learning models at scale from inception to business impact

  • 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!

Pay Grade - L
Equity Grade - 5

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: $133,000 - $183,000

Location - Remote Canada
This remote role is open only to candidates residing in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan.

#LI-Remote

Remote-first with flexibility built in
Affirm is proud to be a remote-first company. Most roles can be done from almost anywhere within the country of employment. Some positions may occasionally require in-person work at an Affirm office, and a few are office-based due to the nature of the work. All new hires will be invited to attend an in-person onboarding experience.

Benefits designed for you
Our benefits reflect our commitment to care, transparency, and flexibility. Here are a few highlights:

  • Health coverage at no cost: We cover 100% of premiums for employees and their dependents.
  • Spending stipends: Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
  • Time off to recharge: Flexible time off and generous holiday calendars help you rest when you need to.
  • Own a piece of what you build: Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.

We’re committed to providing an inclusive interview process, including accommodations for candidates with disabilities. If you need support, we’re happy to help.

For positions based in San Francisco or Los Angeles: Affirm considers qualified applicants with arrest and conviction records, as required by law.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and consent to the use of your personal information as described.

How we rate this

Machine Learning Engineer II (ROA + LTV ML) at Affirm rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningCredit RiskDeep learningDistributed Systemsscikit-learnXGBoostPythonSQL

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$133k
Typical machine learning engineer job
$197k

This posting starts 33% below the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where credit risk was part of your work. What did you do?
  3. Tell me about a project where deep learning was part of your work. What did you do?
  4. Tell me about a project where distributed systems was part of your work. What did you do?
  5. Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Machine learning, Credit Risk, Deep learning, Distributed Systems, and scikit-learn. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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