About the Team

The mission of the Ads Economics team is to ensure we maintain a healthy ads marketplace across all our verticals for both search (query context) and discovery experiences while fulfilling the requirements of all players in this marketplace.

Ads Economics is a critical part of the Ads Delivery funnel with a broad charter responsible for Bidding, Auction Design, Budget Pacing, Forecasting, and Ads Experimentation. Our work directly shapes advertiser experience, consumer experience, and marketplace balance. We leverage artificial intelligence and advanced ML, deep learning techniques to power decision-making in real time — from optimizing ad auctions to generating the most efficient bids and pacing budgets dynamically. These models sit at the heart of DoorDash’s ad delivery and play a pivotal role in improving the efficiency, fairness, and scalability of our marketplace.

The opportunity is massive as DoorDash expands into new verticals like Grocery and Retail while building unique innovative ad products to leverage the closed loop marketplace. 

About the Role

We’re looking for a Staff Machine Learning Engineer to serve as the technical lead driving the design and development of large-scale ML/optimization systems within the Ads Delivery funnel.

In this role, you will:

• Lead the technical design and implementation of ML solutions for key Ads Economics areas such as Auction, budget pacing, bidding optimization, and forecasting.
• Partner closely with Product, Data Science, and Engineering teams to design experiments, model frameworks, and production ML systems that directly impact advertiser ROI and marketplace efficiency.
• Provide technical mentorship and guidance to engineers and cross-functional partners — leading through influence, not management.
• Build and deploy 0→1 ML systems that improve ad delivery outcomes and marketplace health.
• Set best practices for model training, evaluation, deployment, and monitoring
• Act as a technical thought leader for Ads ML — influencing roadmap, experimentation design, and overall Ads system evolution.

This is a highly impactful IC role for someone who enjoys combining economic intuition, large-scale ML modeling, and system design to solve complex real-world optimization problems.

You're excited about this opportunity because you will…

• Own impactful ML systems: Build and improve models that directly have a large impact on top and bottom line financials.
• Drive experimentation: Rapidly test hypotheses via robust sequential experiments; measure and explain your models’ impact on marketplace KPIs
• Optimize at scale: Work with one of the largest delivery datasets, building optimization pipelines that consider budget, fairness, assignment rates, and more
• Collaborate cross-functionally: Partner with engineering, analytics, product, and operations to iterate quickly, moving models from prototype to production
• Shape the future: We're one of the fastest growing Ads platforms in the world and we're looking to take that even further

We're excited about you because you have… 

• M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, or a related field.
• 8+ years of industry experience building production-scale ML systems.
• Expertise in at least one of: auction design, pacing, bidding optimization, or forecasting.
• Strong understanding of probability theory, statistics, and machine learning fundamentals.
• Proven ability to lead cross-functional initiatives and drive complex technical projects end-to-end.
• Excellent communication skills — able to explain technical concepts to product, business, and engineering audiences.
• Experience in Ads or marketplace systems is a plus

 

Notice to Applicants for Jobs Located in NYC or Remote Jobs Associated With Office in NYC Only

We use Covey as part of our hiring and/or promotional process for jobs in NYC and certain features may qualify it as an AEDT in NYC. As part of the hiring and/or promotion process, we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound from August 21, 2023, through December 21, 2023, and resumed using Covey Scout for Inbound again on June 29, 2024.

The Covey tool has been reviewed by an independent auditor. Results of the audit may be viewed here: Covey

Compensation

The successful candidate's starting pay will fall within the pay range listed below and is determined