Staff Machine Learning Engineer - Ads Economics

DoorDash USA•San Francisco, CA

19h

About The Position

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

Requirements

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.

Nice To Haves

Experience in Ads or marketplace systems is a plus

Responsibilities

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.

Benefits

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)
medical, dental, and vision benefits
11 paid holidays
disability and basic life insurance
family-forming assistance
a mental health program
flexible paid time off/vacation, plus 80 hours of paid sick time per year
vacation accrued at about 1 hour for every 25.97 hours worked (e.g. about 6.7 hours/month if working 40 hours/week; about 3.4 hours/month if working 20 hours/week), and paid sick time accrued at 1 hour for every 30 hours worked (e.g. about 5.8 hours/month if working 40 hours/week; about 2.9 hours/month if working 20 hours/week)