Manager, Machine Learning Engineering (Underwriting)

Affirm·Remote(Remote US)

AI & Machine Learning

WFA Digital Insight

The demand for skilled machine learning engineers in fintech has surged, with a 25% increase in job openings over the past year. As companies like Affirm pioneer new approaches to credit and lending, experts who can develop and implement advanced ML solutions are in high demand. With its remote-first philosophy, Affirm offers a unique opportunity for leaders to shape the future of machine learning in a flexible, collaborative environment. Before applying, candidates should be prepared to showcase their technical expertise, strategic vision, and ability to thrive in ambiguous environments.

Job Description

About the Role

The Manager, Machine Learning Engineering (Underwriting) plays a pivotal role in Affirm's innovative underwriting machine learning group. This leader will oversee a team of ML engineers responsible for building the economic decisioning engine, leveraging novel ML techniques and rich data representations to underwrite and optimize applications based on expected returns, lifetime value, and predicted conversion. The role involves partnering with engineering, product, and risk leaders to design, implement, and scale advanced ML solutions that drive critical capabilities across the company.

As a key member of the underwriting team, the successful candidate will help shape the future of machine learning at Affirm. They will be responsible for mentoring engineers, bringing clarity to complex, ambiguous problems, and contributing to a cohesive long-term ML strategy. The role requires a unique blend of technical expertise, leadership acumen, and strategic vision.

The underwriting machine learning group is a critical component of Affirm's business, and the Manager, Machine Learning Engineering will be expected to drive technical strategy, collaborate with cross-functional teams, and develop talent within the organization.

What You Will Do

Set the technical strategy for your team, aligning with critical business-impacting projects
Act as a force-multiplier through the definition and advocacy of technical solutions and operational processes
Collaborate across teams in the product development lifecycle, partnering with product management, design, and analytics to ensure technical sustainability, risks, and trade-offs are well understood and managed
Develop and implement novel machine learning models and algorithms to drive underwriting and optimization
Lead the development of large-scale machine learning systems, ensuring scalability, reliability, and maintainability
Provide hands-on technical leadership, working closely with engineers to design and implement complex systems
Communicate technical plans, progress, and results to both technical and non-technical stakeholders
Identify and mitigate technical risks, ensuring the stability and security of Affirm's systems
Stay up-to-date with emerging trends and technologies in machine learning, applying knowledge to drive innovation and improvement

What We Are Looking For

Bachelor's degree in a technical field with 8+ years of industry experience, including 3+ years managing engineers
Proficiency in machine learning, with experience in areas including tree-based models, transformers, deep learning, and agentic ML
Strong engineering skills, with the ability to provide hands-on technical leadership while working with code and architecture
Experience working in ambiguous environments, with the ability to move from low-level language idioms to the architecture of large systems
Excellent communication and leadership skills, with the ability to mentor and develop talent within the organization
Experience working with cross-functional teams, including product management, design, and analytics
Strong understanding of technical sustainability, risks, and trade-offs, with the ability to communicate complex technical concepts to non-technical stakeholders

Nice to Have

Experience working in fintech or a related industry, with a deep understanding of underwriting and optimization
Knowledge of cloud-based technologies, including AWS or Google Cloud
Experience with containerization using Docker, and orchestration using Kubernetes
Familiarity with agile development methodologies, including Scrum or Kanban
Experience working with remote teams, with a strong understanding of the challenges and opportunities of remote collaboration

Benefits and Perks

Competitive base salary, with a range of $200,000 - $275,000 per year depending on location and experience
Equity rewards, with a focus on long-term growth and success
Monthly stipends for health, wellness, and tech spending
100% subsidized medical coverage, dental, and vision for you and your dependents
Flexible PTO policy, with a focus on work-life balance and employee well-being
Remote work stipend, with the opportunity to work from anywhere in the US
Professional development opportunities, with a focus on continuous learning and growth
Access to cutting-edge technologies and tools, with the opportunity to work on complex and challenging projects

How to Stand Out

Tip: Showcase your technical expertise in machine learning, with a focus on novel ML techniques and rich data representations.
Be prepared to discuss your experience working in ambiguous environments, and how you communicate complex technical concepts to non-technical stakeholders.
Highlight your ability to mentor and develop talent within the organization, with a focus on leadership and strategic vision.
Familiarize yourself with Affirm's products and services, and be prepared to discuss how your skills and experience align with the company's mission and values.
Prepare to discuss your experience working with cross-functional teams, including product management, design, and analytics.
Research the company culture and values, and be prepared to discuss how you would contribute to and thrive in a remote-first environment.

This is a remote position listed on WFA Digital, the platform for professionals who work from anywhere. Browse more remote jobs across all categories.