Machine Learning Engineering Manager, Credit & Underwriting

Description

The company is the company, a financial technology platform offering payments, data and financial products in one solution to customers such as Meta, Uber, H&M and Microsoft.

The Financial Products group is building the infrastructure that lets customers manage money, issue cards and access credit and financing worldwide.

A new Machine Learning Engineering team is being formed in San Francisco to focus on credit risk modeling for underwriting. Its work supports scaling the company's credit products 100x.

You will lead the Credit Risk Modeling team, which builds and runs machine learning models and rule-based decision systems for credit products. The work covers the whole model lifecycle: research, data analysis, training, deployment, monitoring and ongoing improvement.

The team is made up of machine learning scientists and data engineers. You will coach them, improve how the team runs its engineering work, and help shape the team's culture so it grows future leaders.

Responsibilities

• Lead the team with hands-on technical involvement, setting architecture direction and raising technical standards through mentoring and guidance.
• Coach team members on engineering practices, scalable architecture and product roadmap decisions so each person grows.
• Set individual and team goals that match the engineering strategy, working closely with the product manager.
• Refine product requirements with product and merchant stakeholders, and work with design, product engineering, data engineering and credit operations.
• Help design and build new pipelines and services with reliability, infrastructure, data and developer needs in mind.
• Build an open, inclusive culture based on autonomy, ownership, collaboration, communication and impact, with regular feedback.
• Recruit people who fit the company culture and have the skills the team needs.

Requirements

• Proven experience with machine learning products and a deep understanding of how they work.
• An energetic, self-driven approach and a record of getting several teams aligned.
• Ability to define success metrics, track performance and spot where existing systems can improve.
• Experience coaching and mentoring engineers.
• Experience leading technical projects in a fast-moving, high-stakes setting.
• Experience working with senior leaders to set strategy, including product roadmaps.
• Strong communication skills, and the ability to explain technical ideas to non-engineers.
• At least 2 years managing machine learning engineering teams in a mission-critical environment.
• At least 7 years working in a machine learning or AI technology environment.
• Experience with credit underwriting.

Conditions

Based in San Francisco.

Equal opportunity statement: applicants are considered without regard to protected characteristics.