Staff Machine Learning Engineer, Money (Founding ML Lead)

DoorDash USA • Los Angeles, CA

4h

About The Position

The Money org at DoorDash builds the financial products and platforms that power our marketplace — from helping merchants grow their businesses with access to capital, to enabling banking products for Dashers, to optimizing consumer payments and checkout experiences.
We are forming a new Money Machine Learning team, and this role will be the founding ML engineer. The team’s initial focus will be on underwriting and decisioning for merchant cash advances and lending products, with a broader mandate over time to support other high-impact Money initiatives, including:
Merchant, Dasher and Consumer financial products (banking, payouts, gift cards, risk)
Consumer payments optimization (authorization rates, routing, cost efficiency)
Platform-level ML capabilities for credit and financial decisioning
This team will sit at the intersection of fintech bets and the Money platform, building reusable ML systems that scale across products. Over time, this role has the opportunity to grow and shape a team, setting technical direction and best practices for financial ML at DoorDash.
We’re looking for a Staff Machine Learning Engineer to lead the design, development, and deployment of production-grade ML systems that drive financial decisioning across DoorDash’s Money ecosystem.
You will start by owning ML-driven underwriting models for merchant cash advances, partnering closely with Product, Risk, Data Science, and Engineering to improve approval rates, loss performance, and capital efficiency. As the Money ML surface area expands, you will broaden your scope to support additional initiatives such as banking products, payouts, and consumer payments optimization.
This is a highly impactful individual contributor role for someone who enjoys building 0→1 ML systems, operating at Staff-level scope, and influencing technical direction across multiple teams. You will play a key role in setting best practices for model development, deployment, monitoring, and governance across the Money org.
You’re excited about this opportunity because you will…
Own and build foundational ML systems that directly impact capital allocation, risk, and growth across DoorDash.
Work on real-world financial decisioning problems, including credit and underwriting, with clear business and customer impact.
Lead 0→1 ML initiatives, defining how machine learning is applied across Money products.
Operate at Staff-level scope, influencing architecture, strategy, and execution beyond a single team.
Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.
Help shape the future of Money ML at DoorDash, with the opportunity to mentor others and grow a team over time.

Requirements

• You have 8+ years of industry experience building and deploying production-scale ML systems.
• You have direct experience with credit, lending, or cash advance underwriting, including risk modeling and decisioning.
• You have a strong foundation in statistics, probability, and machine learning, and know how to apply them to noisy, real-world financial data.
• You are fluent in Python (and/or Java, Scala, or C++) and experienced with ML frameworks such as XGBoost, PyTorch, TensorFlow, or similar.
• You have designed and operated ML systems in production, including monitoring, retraining, and model governance.
• You can lead complex technical projects end-to-end, influencing stakeholders across multiple orgs.
• You communicate clearly and effectively with technical and non-technical audiences.
• You are excited about building something new and operating with ambiguity at high ownership.

Nice To Haves

• Experience in fintech, payments, banking, or marketplace risk systems is a strong plus.

Responsibilities

• Own and build foundational ML systems that directly impact capital allocation, risk, and growth across DoorDash.
• Work on real-world financial decisioning problems, including credit and underwriting, with clear business and customer impact.
• Lead 0→1 ML initiatives, defining how machine learning is applied across Money products.
• Operate at Staff-level scope, influencing architecture, strategy, and execution beyond a single team.
• Collaborate closely with Product, Data Science, and Platform Engineering in a highly cross-functional environment.
• Help shape the future of Money ML at DoorDash, with the opportunity to mentor others and grow a team over time.

Benefits

• comprehensive benefits package to all regular employees, which includes a 401(k) plan with employer matching
• 16 weeks of paid parental leave
• wellness benefits
• commuter benefits match
• paid time off and paid sick leave in compliance with applicable laws (e.g. Colorado Healthy Families and Workplaces Act)
• DoorDash also offers medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program, among others.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed