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Machine Learning Engineer II (ROA + LTV ML)

Pay
$133,000–183,000/year · Base — pay source
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.
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Work setting
Remote — work setting source
Listed location: Remote Canada
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Employment
Not stated

What you’ll work on

Full posting
  • Develop ML models that predict default likelihood and drive approve or decline decisions

  • Build model training, decisioning, and monitoring systems with platform and product engineers

  • Research and prototype new approaches to credit decisioning

  • Implement and scale data pipelines, features, and algorithms for production models

  • Define requirements for new products with engineering, credit, and product teams

From the employer’s posting
develop machine learning models that predict the likelihood of default and make an approval or decline decision
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
Education & alternatives
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
Apply at Affirm

Posting record

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Status in our records
Live
First seen by us
Oct 16, 202618 days ago
Recorded sightings
52
Last seen by us
Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 18

Similar jobs usually come down between day 6 and day 69.

From 4,301 similar postings that came down. Coming down is not always a hire.

Affirm is hiring

17 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Takes jobs down at a usual pace
  • 6% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • NumPy
  • pandas
  • scikit-learn
  • XGBoost
Where the posting names them
- 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 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

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About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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.

Source details

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Pay
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.
Location & working pattern

Remote Canada

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:
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