Manager, Machine Learning Engineering (Repayment & Recovery)
AI & Machine Learning
WFA Digital Insight
As demand for machine learning specialists in financial services grows, Affirm is seeking a seasoned leader to drive their repayment and recovery efforts. With the global ML market expected to reach
58 billion by 2025, professionals with expertise in tree-based models, transformers, and deep learning are in high demand. Affirm's commitment to remote work and transparent pay structures makes this role particularly attractive. Candidates should be prepared to showcase their technical leadership and experience in post-origination modeling.
Job Description
About the Role
Affirm is revolutionizing the credit industry by providing consumers with flexible, transparent payment options. As a Manager of Machine Learning Engineering, you will play a pivotal role in shaping the company's repayment and recovery strategies. Your team will develop and implement machine learning models that predict repayment behavior, prioritize collections, and minimize loss. You will collaborate with cross-functional teams, including engineering, product, and risk, to drive business-impacting projects.The successful candidate will have a strong technical background, with experience in machine learning and a proven track record of leading high-performing teams. You will be responsible for setting the technical strategy for your team, mentoring engineers, and contributing to the company's overall ML strategy.
What You Will Do
- Set the technical strategy for your team and align it with critical business objectives
- Manage a team of ML engineers and provide guidance on technical projects
- Collaborate with product management, design, analytics, and risk teams to ensure technical sustainability and risk management
- Develop and implement machine learning models that drive repayment and recovery efforts
- Provide feedback and guidance to engineers and lead by example
- Partner with engineering leaders to design, implement, and scale advanced ML solutions
- Contribute to the company's overall ML strategy and technical direction
- Stay up-to-date with industry trends and emerging technologies in machine learning
What We Are Looking For
- Bachelor's degree in a technical field with 8+ years of industry experience
- 3+ years of experience managing engineers and leading technical teams
- Background in financial services, specifically in credit/lending, with hands-on experience in post-origination modeling
- Proficiency in machine learning with experience in tree-based models, transformers, deep learning, and agentic ML
- Strong engineering skills and ability to provide hands-on technical leadership
- Experience working with cross-functional teams and collaborating with stakeholders
- Ability to thrive in ambiguity and navigate complex technical problems
Nice to Have
- Experience working in a remote-first company and leading distributed teams
- Familiarity with cloud-based technologies and containerization
- Knowledge of data visualization tools and techniques
- Experience with agile development methodologies and Version control systems
Benefits and Perks
- Competitive base salary and equity package
- Comprehensive health, dental, and vision benefits for you and your dependents
- Remote work stipend and flexible working hours
- Opportunities for professional growth and career development
- Access to cutting-edge technologies and tools
- Collaborative and dynamic work environment
- Recognition and reward for outstanding performance
How to Stand Out
- Develop a strong understanding of machine learning concepts and algorithms, particularly in the context of financial services.
- Showcase your experience in leading technical teams and collaborating with cross-functional stakeholders.
- Be prepared to discuss your approach to problem-solving and navigating complex technical challenges.
- Highlight your ability to communicate technical concepts to non-technical stakeholders.
- Research Affirm's company culture and values to demonstrate your alignment with their mission.
- Prepare examples of your experience working with machine learning models and data visualization tools.
- Be ready to discuss your salary expectations and negotiate based on industry standards.
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