Affirm
Machine Learning Engineer II (ROA + LTV ML)
Remote Canada · Mid
Sponsorship not specified$133k-$183kDetected 4 days ago
PythonDistributed SystemsAlgorithmsSQLRESTMachine LearningDeep Learningscikit-learnPandasNumPySparkData EngineeringResearchCommunicationGeneralized Linear Models
Stay score
odds of building a lasting career here
57Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card follow-through: 71%
Of 7 labor certifications old enough to have been used, 2 expired without the employer filing the next step. Median time from filing to decision: 497 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
12 transfer filings in the last year, covering 12 workers. Median labor-condition decision: 8 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
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About the role
- 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!
- Pay Grade - L Equity Grade - 5 Employees new to Affirm typically come in at the start of the pay range.
Responsibilities
- 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
- 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!
- Own a piece of what you build:
- If you need support, we're happy to help.
Requirements
- Affirm considers qualified applicants with arrest and conviction records, as required by law.
Compensation
- Employees new to Affirm typically come in at the start of the pay range.
- CAN base pay range per year: $133,000 - $183,000
Benefits
- Our benefits reflect our commitment to care, transparency, and flexibility.
- Health coverage at no cost:
- Monthly stipends support your tech setup, and the ability to choose health and wellness options that are right for you.
- Flexible time off and generous holiday calendars help you rest when you need to.
- Our employee stock purchase plan (ESPP) lets you buy Affirm stock at a discount.
- 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
- 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.
- Experience developing machine learning models at scale from inception to business impact
- In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).
Company info
- 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.
This listing is sourced directly from Affirm's careers page and normalized into a canonical job model.