Senior Machine Learning Engineer

Affirm; Saskatoon; Remote; CAD 150,000 - 200,000; Full time

Job summary

A leading company in financial technology is seeking a Machine Learning Engineer to join their ML Underwriting team. You will develop high-quality models that assess creditworthiness and impact decision-making processes. This role requires expertise in machine learning and a collaborative spirit to drive innovation in credit decisioning.

Benefits

100% subsidized medical coverage

Flexible Spending Wallets

Competitive vacation and holiday schedules

Employee stock purchase plan

Qualifications

• 6+ years of experience as a machine learning engineer.
• Experience developing machine learning models at scale.
• Strong engineering skills in Python and data manipulation.

Responsibilities

• Develop machine learning models to predict default likelihood.
• Collaborate with product and engineering teams on model training.
• Implement and scale data pipelines and algorithms.

Skills

Machine Learning

Python

Data Manipulation

Communication

Education

PhD in relevant field

Tools

scikit-learn

pandas

NumPy

XGBoost

PyTorch

Kubeflow

Kubernetes

Docker

Airflow

Job description

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Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest.

Join the Affirm team as a Machine Learning Engineer and contribute to the success of our ML Underwriting team. We are the driving force behind Affirm's core value proposition, leveraging cutting-edge machine learning to assess creditworthiness throughout the life cycle of loan applications. 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

• 6+ years of experience as a machine learning engineer. Relevant PhD can count for up to 2 YOE
• 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.
• Strong engineering skills in Python and data manipulation skills like SQL
• 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

Pay Grade - N

Equity Grade - 6

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 : $150,000 - $200,000

Affirm is proud to be a remote-first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include :

• Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents
• Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses
• Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge
• ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.

By clicking "Submit Application," you acknowledge that you have read Affirm's Global Candidate Privacy Notice and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

Seniority level

Seniority level

Mid-Senior level

Employment type

Employment type

Full-time

Job function

Job function

Engineering and Information Technology

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